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This study aimed to investigate the effect of soil–structure interaction (SSI) on the inelastic displacement ratio of bridge structures subjected to near-fault pulse-like earthquake ground motions. SSI was modeled using a discrete-time recursive filter approach and frequency-dependent foundation–soil impedance functions. A total of 105 near-fault earthquake ground motion records were used for the analysis. The study also compared the soil–foundation–superstructure (SFS) system with a fixed-base system to explore the effects of spectral period normalization, strength reduction factor, earthquake magnitude, site-to-source distance, and peak ground velocity on the inelastic displacement ratio. The findings indicate that both the SFS and fixed-base systems have significant inelastic displacement demand under near-fault earthquakes, with values that can be 2–3 times higher than those predicted by ASCE-41-13, particularly in the short period range. Furthermore, as the structural period approaches the earthquake pulse period, the SFS system generally shows larger inelastic displacement ratios compared to the fixed-base system. The analytical results provide insight into the factors affecting the inelastic displacement ratio for near-fault pulse-like earthquakes. [ABSTRACT FROM AUTHOR]

Pre-processing of the photoplethysmography (PPG) signal plays an important role in the analysis of the pulse wave signal. The task of pre-processing is to remove noise from the PPG signal, as well as to transmit the signal without any distortions for further analysis. The integrity of the pulse waveform is essential since many cardiovascular parameters are calculated from it using morphological analysis. Digital filters with infinite impulse response (IIR) are widely used in the processing of PPG signals. However, such filters tend to change the pulse waveform. The aim of this work is to quantify the PPG signal distortions that occur during IIR filtering in order to select a most suitable filter and its parameters. To do this, we collected raw finger PPG signals from 20 healthy volunteers and processed them by 5 main digital IIR filters (Butterworth, Bessel, Elliptic, Chebyshev type I and type II) with varying parameters. The upper cutoff frequency varied from 2 to 10 Hz and the filter order—from 2nd to 6th. To assess distortions of the pulse waveform, we used the following indices: skewness signal quality index (SSQI), reflection index (RI) and ejection time compensated (ETc). It was found that a decrease in the upper cutoff frequency leads to damping of the dicrotic notch and a phase shift of the pulse wave signal. The minimal distortions of a PPG signal are observed when using Butterworth, Bessel and Elliptic filters of the 2nd order. Therefore, we can recommend these filters for use in applications aimed at morphological analysis of finger PPG waveforms of healthy subjects. [ABSTRACT FROM AUTHOR]

In this paper, a behavioral model for the variable gain amplifiers working in the liner region is proposed. An iterative least‐square algorithm for complex curve fitting is proposed to model the variable gain amplifiers as an infinite impulse response filter. The polynomial fittings are used to obtain the coefficient matrix for the gain response and phase response to the frequency at different control voltages. The relationship between gain and control voltage is fitted by a hyperbolic tangent function. The modeling flow is given in this paper. Comparing the frequency response of the behavioral model and circuit model, the simulation results are similar at the operating frequency. Finally, an application is given, which is used to compare the effect of the nonlinear phase system with two different band signals modulated by 4QAM. This application proves that the model can be used in the simulation of large‐scale systems. [ABSTRACT FROM AUTHOR]

The potential of filter algorithms in improving spectral model performance was evaluated. A total of 329 animal and vegetable oil samples were used to collect attenuated total reflectance – Fourier transform infrared (ATR-FTIR) spectra. Fisher discriminant analysis (FDA), support vector machine (SVM), decision tree (DT), K-nearest neighbor analysis (KNN), and multilayer perceptron neural network (MLP) were considered to build models. Three filter algorithms, finite length unit impulse response filter (FIR), infinite length impulse response filter (IIR) and wavelet transform (WT), were evaluated to enhance the performance of the models. The Morlet basis function was the most suitable wavelet transform, accurately classifying 90.3% of the training set and 94.4% of the test set. The MLP algorithms were demonstrated to be superior to the others. The best performance was obtained using low-pass or band-stop filters that provided 100% accuracy with the MLP model. The reported method is demonstrated to be affordable and easy-to-use in forensic analysis. [ABSTRACT FROM AUTHOR]

In the field of science and engineering, significant attention can be observed recently for system identification as a complex optimization problem. As the infinite impulse response (IIR) models can achieve more accurate models of physical plants for real-world applications, they are mostly preferred over finite impulse response models. Despite the latter advantage of the IIR structures, it is not straightforward to minimize the related cost functions as they tend to generate multimodal error surfaces. Metaheuristic algorithms have already been shown for their excellent promise to deal with such difficulties as they operate independent of the nature of the problem. In this regard, this work aims to demonstrate the excellent promise of a novel developed metaheuristic algorithm named pattern search ameliorated arithmetic optimization algorithm. The proposed algorithm integrates the original form of the arithmetic optimization algorithm (for exploration) with the pattern search algorithm (for exploitation) such that a better-performing metaheuristic structure is achieved. The excellent ability of the proposed pattern search ameliorated arithmetic optimization algorithm is demonstrated against the original arithmetic optimization algorithm by using well-known classical benchmark functions and welded beam design problem. A significant improvement is achieved for benchmark functions, and an improvement of up to 25% is obtained for the optimal cost of the welded beam design. Then, different IIR model identification problems are considered, and a comparative assessment is performed using different metaheuristic optimization techniques: particle swarm optimization algorithm, artificial bee colony algorithm, electromagnetism-like optimization algorithm, cuckoo search algorithm, and flower pollination algorithm. The obtained statistical results from different systems confirm that the pattern search ameliorated arithmetic optimization algorithm can achieve better accuracy and robustness in terms of IIR model identification. [ABSTRACT FROM AUTHOR]

This paper aims to develop a high-performance method for designing Finite Impulse Response (FIR) filters that effectively control the over-frequency response parameters. The proposed approach involves designing an optimal FIR filter based on an Infinite Impulse Response (IIR) filter, considering various parameters such as pass and stop band ripples, stop band attenuation, transition bandwidth, and linear phase response. The advantages of the IIR filter's better frequency response are utilized in this design. The parameters of Butterworth and Chebyshev filters are optimized using Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) algorithms, incorporating novel fitness functions based on different distance metrics. Visual examination of the filtered signals shows that the proposed algorithm reduces phase delay compared to traditional filters. Additionally, the performance of the designed filter is evaluated by decomposing a sinusoidal signal with four different frequencies into its sub-bands. The numerical results demonstrate that the proposed approach achieves more precise decomposition compared to commonly used traditional filters. [ABSTRACT FROM AUTHOR]

Many works in the state of the art are interested in the increase of the camera depth of field (DoF) via the joint optimization of an optical component (typically a phase mask) and a digital processing step with an infinite deconvolution support or a neural network. This can be used either to see sharp objects from a greater distance or to reduce manufacturing costs due to tolerance regarding the sensor position. Here, we study the case of an embedded processing with only one convolution with a finite kernel size. The finite impulse response (FIR) filter coefficients are learned or computed based on a Wiener filter paradigm. It involves an optical model typical of codesigned systems for DoF extension and a scene power spectral density, which is either learned or modeled. We compare different FIR filters and present a method for dimensioning their sizes prior to a joint optimization. We also show that, among the filters compared, the learning approach enables an easy adaptation to a database, but the other approaches are equally robust. [ABSTRACT FROM AUTHOR]

Digital filter design optimization counts as one of the most challenging problems in circuit development. Furthermore, the bit-width allocation has a crucial impact on the efficiency and accuracy of fixed-point digital filters. The conventional implementation procedure involves studying the bit-width allocation problem after determining the filter coefficients. This sequential procedure leads frequently to an excessive bit-width allocation, hence an extra implementation cost. The main contribution of this paper is to propose a new implementation procedure based on the simultaneous handling of both design issues and the bit-width optimization for the infinite impulse response filter. In this study, the problem is formalized by a multi-objective programming technique using the non-dominated sorting genetic algorithm II. The joint consideration of the two problems offers a better trade-off between design and bit-width allocation. The output of our approach is compared to the results of existing algorithms. Simulation results show that the multi-objective method significantly reduces the implementation cost while ensuring filter stability and an acceptable mean square error (MSE) compared to the existing algorithms. [ABSTRACT FROM AUTHOR]

A design method for the allpass-based infinite impulse response multi-notch filters with identical pole radiuses is derived in the paper. According to the standard procedure when design of the allpass-based filters is considered, the multi-notch filters' magnitude response specifications are first formulated as the phase response specifications of the corresponding allpass filter. Then, for the specified identical pole radiuses, it is shown that unknown allpass filter coefficients can be obtained determined from the square system of linear equations. On the other hand, the minimum value of the pole radius, such that specifications of the the magnitude response are satisfied in all passbands, can be determined using the bisection method. Results of comparison with some of the existing design methods lead to the conclusion that proposed filters have higher area under the squared passbands magnitude response compared to filters with the same maximum pole radius. Furthermore, utilization of the proposed method can result in transfer functions that have the lowest possible maximum pole radius. [ABSTRACT FROM AUTHOR]

The use of floating-point units (FPU) in digital signal processing has increased due to the range and the high precision numbers that can be represented. These units are required in image processing, digital filters with infinite impulse response (IIR), finite impulse response (FIR), and digital controllers, to obtain accurate results and avoid unstable responses, however, to implement them, some processors have built-in units, this implies a technological dependency of the manufacturers when prototypes are developed. To avoid such dependency, this article presents the design of modules for the most used operations in digital signal processing: multiplication and addition/subtraction. To be able to implement these operations in any Field Programmable Gate Array (FPGA), the steps and considerations to be aware of are presented, such as exceptions, rounding, and normalization of operands. Results are verified using the MODELSIM® test bench and the error rate was determined using MATLAB®. [ABSTRACT FROM AUTHOR]

High-level synthesis of data paths in digital filters and model identification tasks are a most complicated optimization problem. Generally, the use of infinite impulse response (IIR) models for identification is chosen over their equivalent finite impulse response (FIR) models, because the former yield more perfect models of physical plants for real-world optimization problems. Additionally, infinite impulse response (IIR) model structures tend to make various multimodal error surfaces whose objective cost of the problems is significantly more difficult to minimize. For the solution of these types of issues, we needed more powerful methods that could resolve it perfectly. In this study, a novel hybrid variant of chimp and cuckoo search method has been developed for IIR related large-scale optimization issues, and it is known as chimp–cuckoo search algorithm (ChCS). The strength of the proposed method has been tested on the 23 standard functions and three types of infinite impulse response (IIR) models. Meanwhile, the numerical and statistical tabulated solutions of the ChCS method are also presented, showing the advantages of the proposed method over the competitors. [ABSTRACT FROM AUTHOR]

We describe a custom and open source field-programmable gate array (FPGA)-based data acquisition (DAQ) system developed for electrophysiology and generally useful for closed-loop feedback experiments. FPGA acquisition and processing are combined with high-speed analog and digital converters to enable real-time feedback. The digital approach eases experimental setup and repeatability by allowing for system identification and in situ tuning of filter bandwidths. The FPGA system includes I2C and serial peripheral interface controllers, 1 GiB dynamic RAM for data buffering, and a USB3 interface to Python software. The DAQ system uses common HDMI connectors to support daughtercards that can be customized for a given experiment to make the system modular and expandable. The FPGA-based digital signal processing (DSP) is used to generate fourth-order digital infinite impulse response filters and feedback with microsecond latency. The FPGA-based DSP and an analog inner-loop are demonstrated via an experiment that rapidly steps the voltage of a capacitor isolated from the system by a considerable resistance using a feedback approach that adjusts the driving voltage based on the digitized capacitor current. [ABSTRACT FROM AUTHOR]

There exist several methods aimed at human–robot physical interaction (HRpI) to provide physical therapy in patients. The use of haptics has become an option to display forces along a given path so as to it guides the physiotherapist protocol. Critical in this regard is the motion control for haptic guidance to convey the specifications of the clinical protocol. Given the inherent patient variability, a conclusive demand of these HRpI methods is the need to modify online its response with neither rejecting nor neglecting interaction forces but to process them as patient interaction. In this paper, considering the nonlinear dynamics of the robot interacting bilaterally with a patient, we propose a novel adaptive control to guarantee stable haptic guidance by processing the causality of patient interaction forces, despite unknown robot dynamics and uncertainties. The controller implements radial basis neural network with daughter RASP1 wavelets activation function to identify the coupled interaction dynamics. For an efficient online implementation, an output infinite impulse response filter prunes negligible signals and nodes to deal with overparametrization. This contributes to adapt online the feedback gains of a globally stable discrete PID regulator to yield stiffness control, so the user is guided within a perceptual force field. Effectiveness of the proposed method is verified in real-time bimanual human-in-the-loop experiments. [ABSTRACT FROM AUTHOR]

Autocalibration signal is acquired in the k-space-based parallel MRI reconstruction for estimating interpolation coefficients and reconstructing missing unacquired data. Many ACS lines can suppress aliasing artifacts and noise by covering the low-frequency signal region. However, more ACS lines will delay the data acquisition process and therefore elongate the scan time. Furthermore, a single interpolator is often used for recovering missing k-space data, and model error may exist if the single interpolator size is not selected appropriately. In this work, based on the idea of the disagreement-based semi-supervised learning, a dual-interpolator strategy is proposed to collaboratively reconstruct missing k-space data. Two interpolators with different sizes are alternatively applied to estimate and re-estimate missing data in k-space. The disagreement between two interpolators is converged and real missing values are co-estimated from two views. The experimental results show that the proposed method outperforms GRAPPA, SPIRiT, and Nonlinear GRAPPA methods using relatively low number of ACS data, and reduces aliasing artifacts and noise in reconstructed images. [ABSTRACT FROM AUTHOR]

This work presents a cellular neural network (CNN) learning tool based on the Center of Mass Algorithm (CMA), which provides a friendly graphical user interface. As original contributions of this work, the learning tool here developed for CNN features a few adaptations in CMA to improve the training process for grayscale image filtering, such as decreasing learning rates and training with multiple image sets, and comprises many graphical user interface facilities for CNN designers. The training capability of the developed tool is validated through several filter applications, among which lowpass and highpass filters with finite or infinite impulse responses. A comparative analysis is performed between the theoretical responses of the filters and the results obtained from the simulation of a CMOS analog CNN configured by the parameters determined through the learning tool. The training process was very fast for the lowpass filters and acceptable RMS pixel errors have been obtained for all examples, confirming the reliability of the learning tool. [ABSTRACT FROM AUTHOR]

In this work we optimally solve the problem of multiplierless design of second-order Infinite Impulse Response filters with minimum number of adders. Given a frequency specification, we design a stable direct form filter with hardware-aware fixed-point coefficients where all multiplications are replaced by bit shifts and additions. The coefficient design, quantization and implementation, typically conducted independently, are now gathered into one global optimization problem, modeled through integer linear programming and efficiently solved using generic solvers. The optimal filters are implemented within the FloPoCo IP core generator and synthesized for field programmable gate arrays (FPGAs) and application specific integrated circuits (ASICs). With respect to state-of-the-art three-step filter design methods, our one-step design approach achieves, on average, 48% reduction in number of lookup tables, 27% delay reduction and 57% reduction in power on FPGAs. ASICs experiment illustrate similar 48% reduction in circuit area, 27% delay reduction and 65% power reduction for a 14 nm ASIC. [ABSTRACT FROM AUTHOR]

In order to study the application of fuzzy partial fractional-order equation based on infinite impulse response (IIR) digital filter in noise big data monitoring, in this study, first, the noise level is calculated through IIR filter to obtain the sound signal sequence after C weight and A weight; the weight equivalent continuous sound level of C, A, and Z is calculated. Then, the vibration condition of fuzzy partial fractional-order equation is studied; the vibration acceleration signal is converted into the vibration velocity and displacement signal; the corresponding effective values are calculated according to the root mean square (RMS), and the noise monitoring platform is designed from hardware and software aspects. Finally, the calibrated sound level value is compared with the standard signal value generated by the digital signal generator; the sequence of sound signal after weight of the original signal, the actual acceleration signal, velocity signal, and displacement signal are calculated; the acceleration signal, velocity signal, and theoretical signal values are compared at different frequencies. The results show that the error between the calculated and calibrated sound level and the standard signal value is very small, and the results of weight counting of C and A are good and meet the requirement of calculation; the error between the measured value of actual acceleration, velocity, and displacement signal and the theoretical value is small, which can realize the accurate acquisition of vibration signal; the error between the actual measured value and the theoretical value of acceleration and velocity at different frequencies is small, about 1% and 10%, respectively. Therefore, the fuzzy partial fractional-order equation based on IIR digital filter can effectively monitor the big noise data. [ABSTRACT FROM AUTHOR]

Smart structure vibration reduction based on adaptive active vibration control has become a hot research spot in recent years. A filtered-U least mean square algorithm based on an infinite impulse response filter structure is used to solve the interference of controller output to reference signal. The filtered-U least mean square algorithm is very suitable for the nonlinear vibration control of the flexible structure. This study focuses on the analysis and implementation of an adaptive active vibration control system for smart structure with a surface-bonded piezoelectric actuator. The piezoelectric actuator contained in the secondary path has nonlinear hysteresis property. The nonlinear hysteresis property will cause a nonlinear relationship between the structural vibration response and the control voltage, which deteriorates the robustness and control effect of the adaptive control. This study designs an improved version of the filtered-U least mean square algorithm with online hysteresis identification and compensation (filtered-U least mean square–online hysteresis identification and compensation) based on a discrete Prandtl–Ishlinskii model. The Prandtl–Ishlinskii model parameters of the nonlinear hysteresis property are identified online based on the least mean square algorithm. Based on the identified Prandtl–Ishlinskii model parameters, an inverse hysteresis compensator is established for feedforward compensation in the secondary path. Simulation results show that the proposed method can dynamically compensate the hysteresis nonlinearity of the secondary path, linearizing the nonlinear hysteresis. The vibration reduction effect of the proposed method is obviously better than that of other competing methods. A piezoelectric smart cantilever plate with PZT (or lead zirconate titanate, Pb (Zr, Ti)) actuators and sensors is designed to demonstrate the validity and efficiency of the proposed method by experiments. Experiment results demonstrate that the adverse effect of nonlinear hysteresis is eliminated well after feedforward hysteresis compensation is introduced; the unexpected frequency vibration caused by the hysteresis property is suppressed. The proposed methodology possesses an important advantage in application of the adaptive active vibration control of the piezoelectric smart structure. [ABSTRACT FROM AUTHOR]

In this article, a new metaheuristic algorithm named average differential evolution with local search (ADE-LS) has been developed and implemented to find the optimal coefficients of unknown infinite impulse response (IIR) system as a system identifier. The developed method minimizes the error between unknown system output and the adaptive IIR filter output. Rapid convergence is aimed for the global solution in system identification problem using the ADE-LS based adaptive IIR filter modelling with local search. In this way, more precise prediction of filter coefficients is ensured in the filter design with multimodal error surface. ADE-LS algorithm is applied to four benchmarked IIR systems commonly studies in literature to show its performance. Results found by using ADE-LS are compared to other methods reported in terms of convergence rate and the mean square error value. The attained results approve the efficiency of the suggested method. [ABSTRACT FROM AUTHOR]

We address the problem of signal denoising and pattern recognition in processing batch-mode time-series data by combining linear time-invariant filters, orthogonal multiresolution representations, and sparsity-based methods. We propose a novel approach to designing higher-order zero-phase low-pass, high-pass, and band-pass infinite impulse response filters as matrices, using spectral transformation of the state-space representation of digital filters. We also propose a proximal gradient-based technique to factorize a special class of zero-phase high-pass and band-pass digital filters so that the factorization product preserves the zero-phase property of the filter and incorporates a sparse-derivative component of the input in the signal model. To demonstrate applications of our novel filter designs, we validate and propose new signal models to simultaneously denoise and identify patterns of interest. To denoise or detect a pattern of interest in the signal, our proposed signal models simultaneously combine linear time-invariant (LTI) filters and sparsity-based methods with orthogonal multiresolution representations, such as wavelets and short-time Fourier transform. We illustrate the capabilities of our proposed signal models using sleep-electroencephalography (EEG) data to detect K-complexes and sleep spindles. Reproducible research is available at https://github.com/prateekgv/sasdpr. [ABSTRACT FROM AUTHOR]

Human intracranial microwire recordings allow measurement of neuronal activity in human subjects at a fine temporal and spatial scale. The recorded extracellular potentials represent a mixture of action potentials from nearby neurons, local field potentials, and other noise sources. Signal processing of these recordings is used to separate the activity of putative single neurons from other background and noise. To better understand the separation of single neuron activity, one approach is to simulate the signals produced by neurons firing action potentials combined with background activity and noise. This paper characterizes the background activity and noise in human intracranial microwire recordings and presents an accurate and efficient method of simulation using an infinite impulse response filter to color white noise. This method reproduces the power spectral density of the background activity and noise over a frequency range of 1–5000 Hz and is over 200 times faster than previously used methods. It thus facilitates large scale studies of variation of noise sources, field potentials, and processing parameters. It performs equivalently in terms of spike sorting to simulation using white noise. Another advantage is that the simulated signals are known to arise from a pseudorandom number generator and cannot be the result of detecting simulated background spiking activity. This approach provides a rapid and accurate method of simulating background noise and neural activity in human intracranial microwire recordings. It is suitable for use in large scale simulations to study spike sorting in this type of recording. • Spectral properties of human intracranial microwire recordings were characterized. • A 6 pole 5 zero infinite impulse response filter provides an accurate model. • This model is 270 times faster than prior hybrid approaches. • This model allows accurate evaluations of spike sorting performance. • This filter can easily be adapted to other studies of microwire recordings. [ABSTRACT FROM AUTHOR]

The article presents a study that explores the contribution of low contrast–preferring neurons to information representation in the primary visual cortex after learning. It explores the neuronal mechanism using multiple single-unit recordings from deep layers of the primary visual cortex (V1) of trained rats during orientation discrimination.

This letter proposes an online extraction method of common-mode (CM) impedance of induction motor based on all-phase spectrum calculation. All-phase fast Fourier transform with intermediate-frequency filtering (ApFFTIF) is proposed based on infinite impulse response filter, zero-phase filtering technique, and all-phase fast Fourier transform. By using ApFFTIF, the accurate amplitude spectrum together with accurate phase spectrum of CM impedance of induction motor are extracted. Then genetic algorithm is used to establish the model of CM impedance of inductor motor. Finally, through comparing CM impedances extracted by using different spectrum calculation methods, and through comparing measured and calculated CM currents, the accuracy of the proposed method is validated. [ABSTRACT FROM AUTHOR]

The repetitive control (RC) scheme, which can achieve zero steady-state error tracking of any periodic signal with a known integer period, is widely employed in grid-connected inverters to mitigate feed-in current harmonics. However, the conventional RC (CRC) scheme cannot exactly compensate harmonics with fractional period caused by grid frequency variations. Furthermore, the small RC gain of the CRC scheme causes slow transient response. In this article, a proportional-repetitive control (PRC) scheme, which can accommodate a larger RC gain than the CRC scheme, is proposed to provide fast transient response for RC systems. In order to enhance the frequency adaptability of the PRC scheme with a fixed sampling rate, the Thiran all-pass filter, which is a type of infinite impulse response filter for approximating the fractional delay (FD), is used as the FD filter to achieve fast online tuning of the FD and the fast update of the coefficients. The proposed frequency adaptive PRC (FA-PRC) scheme provides grid-connected inverters with a control solution with excellent dynamic performance and accurate frequency adaptability to eliminate harmonic distortion even in the presence of grid frequency variations. A comprehensive series of experiments have demonstrated the effectiveness of the proposed FA-PRC scheme. [ABSTRACT FROM AUTHOR]

Summary: The paper investigates the least‐square design of minimum‐order infinite impulse response multi‐notch filters. Monotonically decreasing nature of the stable allpass filter's phase response, characterizing the allpass‐based multi‐notch filter, along with the simple relation between coefficients and the phase response of the allpass filter, allows the formulation of the multi‐notch filter's magnitude response specifications as the linear equality constraints regarding the positions of notch, left‐ and right‐hand cutoff frequencies. Since the number of such constraints equals triple the number of notch frequencies, while the number of unknown filter coefficients equals double the number of notch frequencies, variable elimination is first performed to ensure that specifications regarding the notch frequencies positions are strictly satisfied. The remaining overdetermined system of linear equations is then solved in the least‐square sense, leading to the approximate satisfaction of left‐ and right‐hand cutoff frequencies positions. Proposed design method is also compared with some of the existing infinite impulse response multi‐notch filter design methods. [ABSTRACT FROM AUTHOR]

Digital filters being the core of digital signal processing systems are categorized into Finite Impulse Response (FIR) filter and Infinite Impulse Response (IIR) filter. Research in this domain shows that both types of digital filters are significant. Digital FIR filters can be designed directly from the required specifications, while digital IIR filters are popularly designed by applying the frequency transformation on the corresponding analog prototype filter. Literature shows the use of wavelets for digital signal processing. The Daubechies wavelets may be recognized as FIR filters with low-pass and high-pass cut-off frequency of 1/2, respectively. The paper attempts to apply digital frequency transformation to meet the desired cut-off frequency to the wavelet coefficients, and in the process, the FIR filter now becomes an IIR filter. The paper compares the response of the IIR filters designed using wavelets with a corresponding IIR filter designed using bilinear transform and the impulse invariant transform of analog Butterworth filters. It is observed that the frequency responses of the IIR filter designed using wavelets and designed using the bilinear transform are comparable. Hence, we have an alternate and simpler method of designing the IIR filters to meet the given specifications. [ABSTRACT FROM AUTHOR]

Objective. The waveform of a photoplethysmography (PPG) signal depends on the measurement site and individual physiological conditions. Filtering can distort the morphology of the original PPG signal waveform and change the timing of pulse feature points on PPG signals. We aim to quantitatively investigate the effect of PPG signal morphology (related to measurement site) and type of pulse feature on the filtering-induced time shift (TS). Approach. 60 s PPG signals were measured from six body sites (finger, wrist under (volar), wrist upper (dorsal), earlobe, and forehead) of 36 healthy adults. Using infinite impulse response digital filters which are common in PPG signal processing, PPG signals were prefiltered (band-pass, pass and stop bands: >0.5 Hz and <0.2 Hz for high-pass filter, <20 Hz and >30 Hz for low-pass filter) and then filtered (low-pass, pass and stop bands: <3 Hz and >5 Hz). Four pulse feature points were defined and extracted (peak, valley, maximal first derivative, and maximal second derivative). For each subject, overall TS and intra-subject TS variability in feature points were calculated as the mean and standard deviation of TS between prefiltered and filtered PPG signals in 50 cardiac cycles. Statistical testing was performed to investigate the effect of measurement site and type of pulse feature on overall TS and intra-subject TS variability. Main results. Measurement site, type of pulse feature, and their interaction had significant impacts on the overall TS and intra-subject TS variability (p < 0.001 for all). Valley and maximal second derivative showed higher overall TS than peak and maximal first derivative. Finger had higher overall TS and lower intra-subject TS variability than other measurement sites. Significance. Measurement site and type of pulse feature can significantly influence the timing of feature points on filtered PPG signals. Filtering parameters should be quoted to support the reproducibility of PPG-related studies. [ABSTRACT FROM AUTHOR]

Recently, a novel population-based optimisation algorithm, namely firefly algorithm (FA), which mimics the flashing and attraction behaviour of fireflies, has shown promising performance in solving global optimisation problems. However, the preliminary studies have shown that FA often gets stuck in local optima. In this paper, we investigate the reasons why the FA suffers from getting stuck in local optima; and then propose an improved firefly algorithm (IFA). These improvements are twofold: first, a sigmoid-based attractiveness is employed to reformulate its definition and strengthen its local refinement ability; second, a dynamic step parameter tuning strategy is designed to adjust the random search intensity and narrow the search space iteratively to strengthen its global search ability. The empirical results indicate IFA can well balance between the global exploration and the local exploitation, and provides the best solutions, at least the competitive results, for most of 12 global optimisation problems over other FA variants. Besides, by employing IFA to solve well-known infinite impulse response filter design problems, we evaluate the effectiveness and efficiency of IFA. The experimental results and comparisons show that IFA performs better than, at least as competent again, other meta-heuristics in terms of the solution accuracy, solution robustness, and convergence rate. [ABSTRACT FROM AUTHOR]

Summary: The discrimination of exons from introns in the DNA sequence of a eukaryotic gene is important to understand the functionality of protein formation inside a living organism. Several signal processing techniques involving transforms and filtering have been used to identify the exon regions by exploring the periodicity‐3 property. Fast processing of massive DNA sequences is desirable to detect the disease‐causing mechanism, which is helpful to prepare individual‐centric drugs. In this manuscript, a hardware implementation is carried out for the direct form‐II structure of the infinite impulse response anti‐notch filter to achieve the fast processing of the DNA sequence. Implementation result on Zynq‐series (Zybo board) Field Programmable Gate Array (FPGA) reveals that the proposed implementation is capable to identify the exon regions of five benchmark eukaryotic genes. The FPGA implementation has achieved a maximum clock frequency of 34.629 MHz, which is further improved to 54.41 MHz using the retiming concept. Compared with MATLAB 2014a simulation, the proposed FPGA implementation has achieved similar accuracy with 39 to 43 times faster computing time for the five benchmark data sets. Further, an Application Specific Integrated Circuit (ASIC) implementation is carried out in the CADENCE Register Transfer Level (RTL) compiler tool with GPDK 90‐nm technology, due to which the hardware anti‐notch filter is 120 to 133 times faster compared with its MATLAB counterpart while maintaining the comparable accuracy. [ABSTRACT FROM AUTHOR]

In this paper, a new method for designing digital infinite impulse response filter with nearly linear-phase response is presented using fractional derivative constraints (FDC). The design problem is constructed as a phase optimization problem between the desired and designed phase response of a filter. In order to achieve the highly accurate passband (pb) response, phase response is fitted to desired response more precisely using FDC, due to which design problem becomes a multimodal error surface that is constructed from sum of passband error (ep) and stopband error (es). Optimal value of FDC is accomplished by minimizing the total error (er0) using improved swarm-based optimization technique, which is formulated by associating the scout bee mechanism of artificial bee colony algorithm with particle swarm optimization and termed as hybrid particle swarm optimization. The simulated results reflect that the improved response in passband along with better transition width is achieved using the proposed method. It is observed that about 90–99% of improvement in passband error can be achieved with 100% reduction in maximum passband ripple. However, slight reduction in stopband attenuation (As), in some cases, results within the permissible limit. The designed filters using this method are also stable toward finite word length effect. [ABSTRACT FROM AUTHOR]

Personal audio systems have been developed based on various approaches with the goal of synthesizing an isolated sound zone that avoids disturbing others in different locations. In this work, a near-field solution for a neckband headset using three loudspeakers positioned close to each ear is proposed. In particular, it is an attempt to derive a simple multichannel filter for reducing the computational cost in mobile devices. Unlike super-directive beamforming techniques, the controlled radiation pattern is not highly directional but can boost the near-field sound, thereby providing an extra sound level difference between the listener's ear locations and far-field surrounding areas. For this purpose, a multichannel filter is designed using a conventional pressure matching technique for reproducing a target signal at the ear location while suppressing sound radiation to a far-field. It is shown that the optimal filter weights can be successfully approximated in the form of a simple broadside differential array pattern. The simplified filter structure can be realized using only two second-order infinite impulse response filters for driving the middle and two side loudspeakers. Through various simulations and experiments, it is demonstrated that the proposed solution can effectively realize a personal audio system with a minimal loss of sound isolation performance. [ABSTRACT FROM AUTHOR]

The article highlights a phase of cortical oscillations determines the perceptual fate of visual cues in naturalistic audiovisual speech. It mentions how brain seamlessly extracts visual cues from their face and processes them along with the sound of their voice, making speech an intrinsically multimodal signal. It also demonstrate that the phase of cortical oscillations acts as an instrument for sensory selection in audiovisual speech processing.

This paper presents a stable, accurate and wideband microwave fractional order differentiator (MFOD) based on infinite impulse response filter. The fractional order differentiator (FOD) design problem is formulated in the z-domain. This formulation alliances with the transmission line elements in cascading. Real coded genetic algorithm (RCGA), particle swarm optimization (PSO) and cuckoo search algorithm (CSA) are applied to determine the optimum values of the characteristic impedances of the transmission line elements. The performance measure criterion of CSA algorithm as compared with other nature inspired algorithms-based differentiator are carried by the magnitude response, absolute magnitude error, phase response, pole-zero response, percentage improvement graph and convergence rate. The simulation and statistical analysis clearly affirm that the proposed MFOD using CSA outperforms RCGA and PSO in all state-of-the-art. The absolute magnitude error for the designed fifth order is as low as 2.9022. The designed fractional order differentiator is implemented in the form of microstrip on RT/Duroid substrate with dielectric constant 2.2 and thickness 0.762 mm. that is eligible for wideband microwave differentiator. The proposed design is compact in size and has low absolute magnitude error over the entire bandwidth. The measured result agrees well with the simulated result in the frequency range 1–12.5 GHz in MATLAB and advanced design software (ADS) environment. [ABSTRACT FROM AUTHOR]

An upsurge in the integration of renewable sources to the utility grid has resulted into escalating concerns regarding power quality (PQ) improvement. In order to provide efficient operation under weak grid conditions, the necessity of a competent control technique is dominant. Consequently, the implementation of an infinite impulse response (IIR) peak filter is used here for harmonics mitigation, power factor correction, and alleviating other PQ issues by providing distribution static compensator (DSTATCOM) capabilities. In addition, this control technique also works during conditions when solar photovoltaic (PV) power is not procurable. During day, the requirement of load is fed from the solar PV array and the stored grid power. On the other hand, at night when the power from solar PV array is unavailable, the requirements of load are fulfilled from the grid and DSTATCOM operation ensures power quality improvement. In order to validate this system, it is maintained according to the IEEE-519 standard. The considered weak grid conditions include load unbalancing, intermittent solar insolation, voltage sag, voltage swell, voltage distortion, and voltage unbalance conditions. The benefits of IIR peak filter include adaptive computation during filtering, thereby alleviating the computational complexity. Moreover, less memory space is required during execution guaranteeing fast performance during weak grid conditions. Simulated results are utilized to depict the behavior of the system during abnormal grid conditions. Moreover, its comparative performance with the existing control techniques, is also presented. For further substantiation and in order to observe reliable operation, a laboratory prototype is developed and tested during weak grid conditions such as voltage distortion, voltage unbalance, voltage sag, voltage swell, and load unbalancing. [ABSTRACT FROM AUTHOR]

Different parameters, which are obtained using classical sensors, are nowadays used to determine the technical state of turbojet engines. In order to expand and to improve this evaluation a novel idea in this area is presented that variations in the near magnetic field of an operational turbojet engine can contain valuable information about its state. Data analysis in different operational states of a small running turbojet engine is presented describing dynamical changes in magnetic induction in the near magnetic field in laboratory conditions. In order to detect the operational state of the engine using magnetic induction derivatives an infinite impulse response filter of the fourth order was designed with cut-off frequency of 2 Hz and expanded by a derivative element. The expanded filter was used to create a linear predictive model, which can be used to compute the rotational speed and exhaust gas temperature of a small turbojet engine using derivatives in magnetic induction in its near magnetic field. [ABSTRACT FROM AUTHOR]

This article aims to provide an efficient fault diagnosis method for gearbox. A self-organizing map–based fault model is developed to provide effective diagnosis of the faults of gearboxes using the gear signals extracted from gearboxes operating with zero and three different types of faults. The gear signals are collected by vibration and acoustic sensors, and pre-denoised using wavelet denoising and wavelet packet decomposition. The characteristic values are subsequently obtained using fast Fourier transform and infinite impulse response filtering. The results showed of the self-organizing map neural network diagnosis model can effectively diagnose gear fault information with a 95% diagnostic accuracy using four input characteristic values: (1) Y-axis vibration displacement amplitude, (2) Y-axis vibration acceleration amplitude, (3) acoustic emission energy amplitude, and (4) acoustic emission signal peak value. The proposed approach provides a novel method to more accurate diagnosis of gear fault pattern and improvement of working efficiency of mechanical instruments. [ABSTRACT FROM AUTHOR]

Infinite impulse response (IIR) system identification problem is defined as an IIR filter modeling to represent an unknown system. During a modeling task, unknown system parameters are estimated by metaheuristic algorithms through the IIR filter. This work deals with the self-adaptive search-equation-based artificial bee colony (SSEABC) algorithm that is adapted to optimal IIR filter design. SSEABC algorithm is a recent and improved variant of artificial bee colony (ABC) algorithm in which appropriate search equation is determined with a self-adaptive strategy. Moreover, the success of the SSEABC algorithm enhanced with a competitive local search selection strategy was proved on benchmark functions in our previous studies. The SSEABC algorithm is utilized in filter modelings which have different cases. In order to demonstrate the performance of the SSEABC algorithm on IIR filter design, we have also used canonical ABC, modified ABC (MABC), best neighbor-guided ABC, and an ABC with an adaptive population size (APABC) algorithms as well as other algorithms in the literature for comparison. The obtained results and the analysis on performance evolution of compared algorithms on several filter design cases indicate that SSEABC outperforms all considered ABC variants and other algorithms in the literature. [ABSTRACT FROM AUTHOR]

Eddy currents can significantly hamper the electromagnetic dynamics, especially those of nonlaminated actuators, and have thus been of great interest in actuator control for many years. Although there are high-fidelity models describing phenomena inside the solid core, such as the magnetic skin effect, these models have never been applied directly within the control circuit. The main reason for this is the lack of an appropriate approximation suitable for time-discrete digital implementation on a microcontroller. This article aims to provide a complete review about possible approaches to obtain a rational approximation of the frequency-dependent effective reluctance and inductance of an electromagnetic actuator. The rational approximation is then used to design a common infinite impulse response filter (IIR-filter). Using the example of a flux-controlled magnetic thrust bearing, we conclude with two novel approximations: a mathematically complex Padé approximation of a sum of continued fractions and a simple Matsuda approximation of an implicit equivalent fractional-order system. On the other hand, the former is the most accurate, and the latter allows wider approximation bandwidths. Depending on possible sampling and switching frequencies as well as the bandwidth of the actuator and computing capacity of the control unit, the most appropriate approximation for almost any use case can be selected. [ABSTRACT FROM AUTHOR]

• The proposed approach can transfer any originally given non-strictly proper filter with distinct poles into parallel-form by using the linear algebra technique without using polynomial long division. • Two computationally efficient parallel-type coupled-form filters in z-domain representation are synthesized. This will lead to a more robust filter, and more importantly, a computationally efficient high-order coupled-form filter for eliminating zero-input limit cycles. • The filter synthesis method we proposed has shown in experiments that, in an n-th order IIR filter, it can reduce the required multiplication calculations to as low as 3n per sampling time. It can also be implemented with very low bit resolution (8 bits) while maintaining excellent output performance. Synthesizing a parallel-form IIR filter from a given non-strictly-proper transfer function requires a polynomial long division method, which results in dynamical range problem under finite word-length (FWL) fixed-point implementations. Based on the state-space similarity transformation, in this paper, a synthesis scheme for parallel-form IIR filters is proposed without requiring long division of polynomials operations to reduce dynamical range problems for obtaining parallelized first or second-order sections either in direct-form or coupled-form. The main advantage of the proposed scheme is that the parallelized IIR filter can be synthesized based on state-space normal-form similarity transformation from any digital filter transfer functions. In addition, the proposed two modified coupled-form filters based on the parallelized IIR filter have benefits of less computational consumption and zero-input limit-cycle free, especially for modified second-order coupled forms in contrast with the conventional coupled-form biquad. Finally, two numerical examples are performed to illustrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Floating point arithmetic circuits provide wide dynamic range and high precision, and they are widely used in scientific computing and signal processing applications, but the complexity increases in hardware implementations of floating point units. In VLSI design architecture, many applications suffer in size of the components used in logical operations. The aim of reducing architecture is to gain reduction in power loss and also in area, but the reduction in size of the components leads to an increase in delay and memory. Hence, to overcome these limitations and to optimize the area, a novel design of floating point processing element (FPPE) architecture is proposed in this work with a smaller number of logical components and registers. A partially folded arithmetic function architecture is modeled for the design of an infinite impulse response (IIR) filter using FPPE and implemented on a field programmable gate array (FPGA) with efficient area. FPGAs are widely used in the implementation of floating point computing modules due to the increase in gate density and embedded arithmetic cores. Synthesis results prove that the proposed design of the IIR filter provides efficient area compared with existing works. The modules are designed in Verilog and implemented on Xilinx FPGAs. [ABSTRACT FROM AUTHOR]

Iterative learning control (ILC) is an effective approach for tracking control system that performs repeating tasks. However, the performance of ILC is significantly deteriorated when the reference is changed. To obtain high tracking performance for both repeating and varying tasks, a novel data-driven tuning method of feedforward controller structured with infinite impulse response (IIR) filter via ILC is developed in this study. Global optimal parameters of the feedforward controller are obtained by linear least-squares method based on the optimal feedforward control force obtained by ILC, while model information is not required. Additionally, to deal with the possible instability problem of the feedforward controller structured with IIR filter, a stable approximation approach on the basis of zero-phase-error tracking algorithm is presented. The stable approximation approach can convert the approximation problem to a convex optimisation problem. Finally, the proposed approach is compared with the standard ILC and a data-driven feedforward control structured with finite impulse response filter by two simulation studies. Simulation results demonstrate that the proposed data-driven feedforward tuning method can achieve high tracking performance and is insensitive to reference variations. [ABSTRACT FROM AUTHOR]

In this paper, a new technique for designing of a stable digital infinite impulse response filter, with improved performance in passband and stopband regions using quantum particle swarm optimization (QPSO) and artificial bee colony (ABC) algorithm, is explored in frequency domain. In the proposed method, QPSO technique is modified with exploiting the novelty of search and replacement mechanism of scout bee from ABC algorithm. For this purpose, a new design problem is constructed as a nonlinear minimization of mean square error between the designed and desired filter responses in passband, stopband, and transition band simultaneously, allowing permissible ripples in passband and stopband. Efficiency of the proposed technique is measured by several attributes like passband error, stopband error, total squared error (SE), maximum stopband attenuation, maximum passband error e pb max , passband ripple, and maximum phase deviation in passband. Experimental results evidence that a significant reduction is achieved in sum of the SE in passband and stopband from 12 to 54%, and the performance is not degraded due to quantization and truncation process. However, computation time in term of CPU time is increased from 0.77 to 4.1%, along with 2.62–7.43% hike in number of function evaluation, when compared to QPSO. A comparative study reveals that the proposed method yields better fidelity parameter as compared other evolutionary algorithms such as gravitational search algorithm, genetic algorithm, and variants of PSO. The proposed technique is also suitable for higher filter taps. [ABSTRACT FROM AUTHOR]

Linear Time Invariant (LTI) filters are often specified and simulated using high-precision software, before being implemented in low-precision fixed-point hardware. A problem is that the hardware does not behave exactly as the simulation due to quantization and rounding issues. This article advocates the construction of LTI architectures that behave as if the computation was performed with infinite accuracy, then converted to the low-precision output format with an error smaller than its least significant bit. This simple specification guarantees the numerical quality of the hardware, even for critical LTI systems. Besides, it is possible to derive the optimal values of all the internal data formats that ensure that the specification is met. This requires a detailed error analysis that captures not only the quantization and rounding errors, but also their infinite accumulation in recursive filters. This generic methodology is detailed for the case of low-precision LTI filters in the Direct Form I implemented in FPGA logic. It is demonstrated by a fully automated and open-source architecture generator tool, and validated on a range of Infinite Impulse Response filters. [ABSTRACT FROM AUTHOR]

Cuckoo search algorithm (CSA) is relatively a new optimization technique with less control parameters and strong exploration ability. Due to the random search associated with CSA, it requires large number of functional evaluations for obtaining optimal solution. An improved algorithm, named as improved global-best-guided CSA, is presented here based on the best solution of previous iteration for the optimal design of multiplierless two-dimensional recursive digital filters. The most important feature of the proposed algorithm is that it is completely self-adaptive with no tuning parameters, whereas in CSA the replacement factor needs to be adjusted. The proposed algorithm exhibits 52% improvement in fitness function evaluation (for p = 2) and the execution time is reduced by 56% in comparison with the existing algorithms. Further, the proposed algorithm has been tested for several benchmark problems and found to exhibit significant performance improvement. [ABSTRACT FROM AUTHOR]

A computational and hardware-efficient second-order infinite impulse response filter structure is proposed in this paper. It can compute discrete cosine transform (DCT) with improved processing speed and is valid for N = 2r, where N is the length of the input sequence and r > 1. A new algorithm is also proposed in this paper which is an improvement over previously reported algorithms in the literature. The proposed algorithm reduces the total number of real multiplications and additions in comparison with the existing algorithms. Using the suggested algorithm, computational cycles required to compute a DCT coefficient are less which further reduces the truncation error while processing a long length of input data. [ABSTRACT FROM AUTHOR]

This work proposes fixed-point hardware architectures for two IIR filters, focusing on design specifications for ECG signal processing, using the truncation error feedback (TEF) to attenuate errors caused by truncation operations inside these recursive structures. The TEF is represented by modulo operation followed by a unit-delay operator and multiplication by a coefficient. In this work, the proposed TEF core consists of a hardware structure based on delay, right-shift and modulo operations. The TEF approach is applied to sequential and parallel IIR filter architectures with fixed and adaptive coefficients. The first structure comprises a first-order high-pass filter applied to attenuate low frequencies of the electrocardiogram (ECG) signal. The second one is a second-order infinite impulse response (IIR) adaptive notch filter used to attenuate power line interference signals. All dedicated architectures were described and simulated using VHDL and synthesized in Cadence environment using the 45 nm Nangate Open Cell Library to verify the results of the area, delay and power metrics. A simulated ECG signal was used as input to check the functionality of the filters. Our results indicate that the TEF approach was useful for both high-pass filter (HPF) and adaptive notch filter (ANF), and it can be a significant strategy to meet design specifications and dynamic performance of fixed-point digital filters. For the synthesis analysis, both HPF and ANF sequential filters had lower power and cell area figures but presented higher normalized power per sample and delay. In summation, the TEF approach enabled the use of fixed-point filters for ECG filtering without degrading their dynamic performance or increasing noise caused by truncation. [ABSTRACT FROM AUTHOR]

Summary: A noniterative method for the all‐pass–based design of infinite impulse response multiple‐notch filters is proposed. This method ensures that specifications regarding positions of notch, left‐ and right‐hand cutoff frequencies, are exactly met, leading to a symmetric magnitude response about notch frequencies. Passband magnitude response can be improved by increasing the order of the corresponding all‐pass filter. A noniterative method for the all‐pass–based design of infinite impulse response (IIR) multiple‐notch filters is proposed. This method ensures that specifications regarding positions of notch, left‐ and right‐hand cutoff frequencies, are exactly met, leading to a symmetric magnitude response about notch frequencies. Passband magnitude response can be improved by increasing the order of the corresponding all‐pass filter. [ABSTRACT FROM AUTHOR]

Abstract The paper presents a pipelined neural IIR filter (PNIIR) for nonlinear speech prediction. It inherits the usual pipelined two layers architecture: the nonlinear modular cascaded subsections and linear combiner subsection, and the nonlinear and linear weights of each module are updated using an real-time learning algorithms. The PNIIR filter units the good tracking performance of the neural IIR network and the low computation load of the pipelined architecture. The performance analysis and complexity analysis are illustrated in this paper. The experimental study for speech prediction is also carried out to testify the efficiency of the proposed nonlinear filter. [ABSTRACT FROM AUTHOR]

The suppression of baseline disturbance in electrocardiogram (ECG) is necessary to avoid distorting diagnostic features in the data. In order to remove baseline drift, digital filter specifications had been designing along with detrending fluctuation algorithms. However, all these methods require a high amount of off-line computation. To address this, we propose a new method to remove baseline drift in ECG signals with semi-real-time computation while compensating for the phase distortion from the frequencies in the passband of the infinite impulse response low-pass filter and estimating its sample delay for the filtered signal. Regarding evaluation of the proposed filter, we can find the fact that the signal-to-noise ratio increases by approximately 3 dB after applying the filter to the MIT-BIH stress data consisted of arrhythmias corrupted with the intentional baseline wander and the disturbances due to muscle interactions as well as electrode-skin impedance mismatch during the electrocardiogram recordings. [ABSTRACT FROM AUTHOR]