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This paper focuses on the numerical study of spherical particle sedimentation, taking into account hydrodynamic interactions. Infinite impulse response (IIR) digital filters, specially tailored to solve the sedimentation dynamics, were used in the present study to numerically solve the coupled ordinary differential equations with the time-dependent coefficients of the problem. Hydrodynamic interactions are modeled using the Rotne–Prager–Yamakawa (RPY) approximation, to which a correction is made to better account for short-range interactions. In order to validate both the proposed numerical resolution method and the RPY correction, this paper begins with the study of two interacting spherical particle sedimentation methods. Comparisons with previously published analytical or numerical results confirm the relevance of the present approach. [ABSTRACT FROM AUTHOR]

This paper first presents six (6) types of benchmark amplitude design specifications, including variable low-pass specification, variable high-pass specification, variable bandpass specification, variable bandstop specification, variable notch-frequency specification, and variable notch-width specification. The design specifications can be taken as typical benchmark specifications targeted at testing as well as validating the effectiveness of various newly developed algorithms for designing various typical variable filters (VFs). Then, the paper provides a novel unity-bounded (UB) function developed for ensuring the stability of those VFs with recursive structures. Finally, a wide variety of simulation results are included for validating the design performance as well as the assured stability by using both the benchmark design specifications and the novel UB function. [ABSTRACT FROM AUTHOR]

In order to accurately predict the lane‐changing trajectory of the vehicle and improve the driving safety of the vehicle, a lane‐changing trajectory prediction model based on the combination of convolutional neural network (CNN) and bidirectional long short‐term memory (BiLSTM) neural network is proposed by comprehensively considering the historical driving behavior, the spatial characteristics of surrounding vehicles and the bidirectional time sequence information of the vehicle trajectory. Firstly, the vehicle trajectory data are filtered and smoothed, and it is divided into three categories: left lane change, right lane change, and straight driving, and a lane change trajectory sample set is constructed. Secondly, CNN‐BiLSTM model is constructed to identify the sample set of lane‐changing trajectory. Considering the interaction between vehicles in the driving process, the information of predicted vehicle, and surrounding vehicles is taken as the input of the model. The extracted feature vector is input to the BiLSTM layer for prediction after the CNN layer feature extraction, and the horizontal and vertical coordinates of the target vehicle at the next time are output. Thirdly, the trajectory data of the US‐101 dataset in NGSIM is selected to verify the performance of the CNN‐BiLSTM model, and at the same time, it is compared with models such as CNN‐LSTM, long short‐term memory (LSTM), BiLSTM, and CNN‐GRU‐Att. Finally, the verification result shows that the overall fitting degree of the vehicle lane change trajectory prediction of the proposed model reaches 99.50%, and the mean square error and mean absolute error are 0.0003076 and 0.01417, which are improved compared with other models. In the meanwhile, the research on multistep trajectory prediction in different prediction time domains is carried out. It was found that the longer the prediction time domain is, the lower the prediction performance of the model decreases, but the prediction accuracy still reached more than 96%, and it was able to accurately predict the lane change trajectory. [ABSTRACT FROM AUTHOR]

With the increasing awareness of environmental protection, the rotary hearth furnace system has emerged as a key technology that facilitates a win-win situation for both environmental protection and enterprise economic benefits. This is attributed to its high flexibility in raw material utilization, capability of directly supplying blast furnaces, low energy consumption, and high zinc removal rate. However, the complexity of the raw material proportioning process coupled with the rotary hearth furnace system's reliance on human labor results in a time-consuming and inefficient process. This paper innovatively introduces an intelligent formula method for proportioning raw materials based on online clustering algorithms and develops an intelligent batching system for rotary hearth furnaces. Firstly, the ingredients of raw materials undergo data preprocessing, which involves using the local outlier factor (LOF) method to detect any abnormal values, using Kalman filtering to smooth the data, and performing one-hot encoding to represent the different kinds of raw materials. Afterwards, the affinity propagation (AP) clustering method is used to evaluate past data on the ingredients of raw materials and their ratios. This analysis aims to extract information based on human experience with ratios and create a library of machine learning formulas. The incremental AP clustering algorithm is utilized to learn new ratio data and continuously update the machine learning formula library. To ensure that the formula meets the actual production performance requirements of the rotary hearth furnace, the machine learning formula is fine-tuned based on expert experience. The integration of machine learning and expert experience demonstrates good flexibility and satisfactory performance in the practical application of intelligent formulas for rotary hearth furnaces. An intelligent batching system is developed and executed at a steel plant in China. It shows an excellent user interface and significantly enhances batching efficiency and product quality. [ABSTRACT FROM AUTHOR]

The research and development of a new disc filter is a key link in intelligent irrigation systems, the core of efficient and water-saving irrigation development, and also an important joint effort to ensure a clean water source in micro-irrigation systems. In this paper, the independent research and development of the fractal flow passage disc filter was taken as the research object, and the disc filter numerical simulation cell (FLUENT) and artificial intelligence technology (Back Propagation Neural Network) were combined to optimize the filter flow channel parameters, including the tilt angle, the length and height of the bottom of the internal section triangle, the taper, the position and number of buffer slots, etc. A new type of disc filter with lower head loss, larger flow capacity, higher filtration efficiency, and longer running time is proposed. It has certain reference value and promotion significance for the future development and design of high-performance disc filters and their wide use. [ABSTRACT FROM AUTHOR]

Maneuvering motion prediction is central to the control and operation of ships, and the application of machine learning algorithms in this field is increasingly prevalent. However, challenges such as extensive training time, complex parameter tuning processes, and heavy reliance on mathematical models pose substantial obstacles to their application. To address these challenges, this paper proposes an LSTM-based modeling algorithm. First, a maneuvering motion model based on a real USV model was constructed, and typical operating conditions were simulated to obtain data. The Ornstein–Uhlenbeck process and the Hidden Markov Model were applied to the simulation data to generate noise and random data loss, respectively, thereby constructing a sample set that reflects real experiment characteristics. The sample data were then pre-processed for training, employing the MaxAbsScaler strategy for data normalization, Kalman filtering and RRF for data smoothing and noise reduction, and Lagrange interpolation for data resampling to enhance the robustness of the training data. Subsequently, based on the USV maneuvering motion model, an LSTM-based black-box motion prediction model was established. An in-depth comparative analysis and discussion of the model's network structure and parameters were conducted, followed by the training of the ship maneuvering motion model using the optimized LSTM model. Generalization tests were then performed on a generalization set under Zigzag and turning conditions to validate the accuracy and generalization performance of the prediction model. [ABSTRACT FROM AUTHOR]

The article presents a study which examines a method for the determination of wave perturbations around tropopause levels using a digital filter. It states that the filtering method can be applied to temperature or refractivity profiles from Global Positioning System (GPS) radio occultation. It is inferred that the method reduces the need for artificial enhancements which is very significant compared to standard filters.

This paper is on the use of a hybrid boundary element method/finite element method (BEM/FEM) to determine the induced electric field in spherical human head models exposed to high-frequency plane electromagnetic (EM) wave. The geometrically simplified models include the homogeneous one and the non-homogeneous one, featuring compartments such as skin, skull, CSF, and brain. Both models are illuminated by plane EM wave at frequencies including 900 and 1800 MHz, 3500 MHz pertaining to 5G communication systems and also 6000 MHz representing the transition frequency related to the EMF safety standards. The numerical results for the electric field induced in both human head models are presented, while the emphasis is on the electric field along the propagation axis. The novelty of this work is related to the subsequent post-processing of the sampled induced field along the model axis by using two different numerical filtering techniques. It is shown that using the peak detection algorithm, the spline interpolation could be used to estimate the signal envelope. The exponentially decaying nature of the envelope allows to assess the penetration depth of the EM radiation within the biological tissue. Moreover, it is shown that the analytically calculated penetration depth, derived for the unbounded medium, is well reproduced by the numerical computation of EM field. [ABSTRACT FROM AUTHOR]

Getting highly accurate output in biomedical data processing concerning biomedical signals and images is impossible because biomedical data are generated from various electronic and electrical resources that can deliver the data with noise. Filtering is widely used for signal and image processing applications in medical, multimedia, communications, biomedical electronics, and computer vision. The biggest problem in biomedical signal and image processing is developing a perfect filter for the system. Digital filters are more advanced in precision and stability than analog filters. Digital filters are getting more attention due to the increasing advancements in digital technologies. Hence, most medical image and signal processing techniques use digital filters for preprocessing tasks. This paper briefly explains various filters used in medical image and signal processing. Matlab is a famous mathematical, analytical software with a platform and built-in tools to design filters and experiment with different inputs. Even though this paper implements filters like, Mean, Median, Weighted Average, Guassian, and Bilateral in Python to verify their performance, a suitable filter can be selected for biomedical applications by comparing their performance. [ABSTRACT FROM AUTHOR]

The multiarea Thévenin equivalent (MATE) solution framework is used in this work to combine several subsystems, which are solved using different multiple and non-multiple time-step sizes. In the proposed asynchronous MATE-multirate (A-MATE-multirate) solution, each subsystem is solved with the integration step size that is most adequate for its own internal time constants. This paper relaxes the requirement of previous multirate techniques, in which the solution time-steps of different systems must be multiples or submultiples of each other. To this end, this paper introduces the concept of asynchronous updating, in which each subsystem is updated according to its own internal clock. This updating process is performed in a closed-form solution, with external subsystems represented by their interpolated Thévenin equivalents. Interpolation with future values without using extrapolation is possible in the electromagnetic transients program solution because the history source for future time-steps is calculated at previous time-steps. The exchange of information between subsystems is conditioned using filters to avoid numerical problems during the decimation of the fast subsystems and the interpolation of the slow subsystems. The effectiveness of the proposed methodology is verified with examples using multiple and non-multiple time-step sizes. [ABSTRACT FROM AUTHOR]

The conversion from a Residue Number System (RNS) to a weighted representation is a costly inter-modulo operation that introduces delay and area overhead to RNS processors, while also increasing power consumption. This paper proposes a new approach to decompose the reverse conversion into operations that can be processed by the arithmetic units already present in the RNS independent channels. This leads to a more effective reuse of the processor circuitry while enhancing parallelism. Experimental results show that, when the proposed techniques are applied to architectures based on ripple-carry adders for the traditional 3-moduli set, the delay is improved in average by 16 percent, the circuit area by 36 percent and the power consumption by 47 percent. When carry-lookahead adder topologies are considered, these improvements are in average of 45 percent for the circuit area and 58 percent for the power consumption while the delay is only slightly reduced. The proposed techniques are applied to a use case in digital filtering, showing an increase in throughput/area of up to 1.25 times, and average reductions in energy consumption of 15.6 percent. This work is a step forward to the usage of RNS in practice, since reverse conversion underpins other hard inter-modulo operations, like comparison, scaling and division. [ABSTRACT FROM AUTHOR]

Active damping is a common way to stabilize the current control of LCL-filtered converters. In this paper, the stable region of −180° phase crossing is first identified within a predefined range of grid impedance and LCL parameter variations. Once the phase of the current control loop is in the identified region, a stabilization control can be attained. Subsequently, digital filters can be adopted to achieve active damping by reshaping the open-loop phase. Various digital filters are selected and benchmarked in this paper. It is confirmed that the all-pass filter has a unity gain and adjustable lagging phase before the Nyquist frequency, thereby being a promising solution to the phase reshaping. Therefore, the all-pass filter is employed to move the phase of the open-loop control (i.e., −180° phase crossing) into the targeted region for active damping. Notably, the current controller and the all-pass filter-based active damping can be separately designed, indicating the easy implementation of the active damping. Experimental tests demonstrate that the proposed method can ensure the system stability over a wide range of parameter variations (e.g., grid impedance changes and LCL-filter parameter drifts) while maintaining fast dynamics with the grid-side current control. [ABSTRACT FROM AUTHOR]

This paper presents the repeated filtering method for finding a smoothed, Bayesian estimate of the path of a stochastic process over a time interval [0, T] when one has used a particle filter to estimate the state of the process. It provides good resolution over [0, T], is easy to implement, and can be used with any sequential importance resampling particle filter regardless of the probabilistic model employed by the stochastic process. Repeated filtering is general, powerful, and simple. It does not require the restrictive assumptions or complex calculations of other methods. It is suitable for real-time operational use in complex situations. We demonstrate the method on two single-target tracking examples. The second of these tracking examples is very difficult to solve by any other method known to us. We then apply repeated filtering to a standard nonlinear time series model that has been used extensively for testing numerical filtering techniques. To further illustrate the power of repeated filtering, we show how adding reflecting boundaries to this time series creates a process that is difficult to smooth with existing techniques but simple with repeated filtering. [ABSTRACT FROM AUTHOR]

Digital spectroscopy with Silicon Photomultiplier (SiPM) array coupled on CsI(Tl) crystal, needs some consideration to achieve desirable energy resolution. an array of SiPMs must be used with large scintillation crystal, therewithal signal from whole SiPMs is not ideal. Also silicon pixels are arranged in arrays at regular intervals. The distances between the pixels and the interference of the cross-talk of adjacent pixels are undesirable factors for energy resolution when the light is received by the crystal and transmitted to the SiPM array. On the other hand, due to the advantages of the SiPM array, there is a need to improve the energy resolution in order to be able to be applied. In this paper, an attempt is made to obtain the desired energy resolution by using the digital spectroscopy method and digital filters and properly shaping the output pulse of the preamplifier by the trapezoidal filter method. In this case, it will be possible to use it in different applications such as spectroscopy by the detector. [ABSTRACT FROM AUTHOR]

This paper proposes a novel evolution strategy for a genetic algorithm (GA). This new algorithm is then applied to design robust D(α, r)-stable infinite-impulse-response (IIR) filters. Unlike existing research on designing IIR filters by using GA, in which the stability of IIR filters is tested by trial and error after the evolution of each generation of a GA, the stability criterion in this paper is embedded within the evolution of each generation. Consequently, the stability of this system can be guaranteed without the need for any other checks of the stability criterion in the evolution of each generation. Numerical experimental results are discussed to illustrate the soundness of the proposed evolution strategy. The robustness of the IIR filters is achieved by ensuring that all poles of the filters are located inside a disk D (α, r) contained in the unit circle, in which α is the center, r is the radius of the disk and ∣α∣ + r < 1. So, in this paper, a D(α, r)-stability criterion will be first derived and then embedded in the GA for the design of robust IIR filters. Finally, two examples will be presented to show that the designed filters remain D(α, r)-stable during the evolution of the GA and will provide satisfactory results. [ABSTRACT FROM AUTHOR]

Recent trends in mobile technology are toward supporting multi-standard communication systems on the same device. This requires their design to be based on some kind of reconfigurable techniques. Also, in cognitive applications, intelligent bandwidth allocation for efficient spectrum utilization requires altering the bandwidth within the same communication channel. Digital filters with non-uniform and varying bandwidths can be used to channelize different frequencies. Efficient designs of such filters are proposed in this paper. Frequency response masking (FRM)-based design is used, where the masking filters can be tuned to a desired set of frequencies by using a variable bandwidth (VBW) digital filter, configured as Farrow structure. For each of the chosen bandwidth, a corresponding masking filter response can be obtained, using the Farrow structure. A novel extension of FRM is proposed in this paper, using two approaches, to realize more than one sharp filter response from the same prototype linear-phase low-pass filter. In both approaches, the masking filters of the FRM filter are realized using Farrow structure. In the first approach, only a set of two Farrow structure filters are required to realize all the required channels. The channel selection is then carried out by varying a single parameter on each of the two masking filters. In the second approach, every channel is realized using a set of two Farrow structure filters and the channel is selected by means of hardware switching techniques. In addition to reconfigurability, hardware implementation complexity of Farrow structure-based VBW is lower compared to the direct FIR filter structure when designed for large set of bandwidths. [ABSTRACT FROM AUTHOR]

The two-dimensional (2-D) system has a wide range of applications in different fields, including satellite meteorological maps, process control, and digital filtering. Therefore, the research on the stability of 2-D systems is of great significance. Considering that multiple systems exist in switching and alternating work in the actual production process, but the system itself often has external perturbation and interference. To solve the above problems, this paper investigates the output feedback robust H8 stabilization for a class of discrete-time 2-D switched systems, which the Roesser model with uncertainties represents. First, sufficient conditions for exponential stability are derived via the average dwell time method, when the system's interference and external input are zero. Furthermore, in the case of introducing the external interference, the weighted robust H8 disturbance attenuation performance of the underlying system is further analyzed. An output feedback controller is then proposed to guarantee that the resulting closed-loop system is exponentially stable and has a prescribed disturbance attenuation level γ. All theorems mentioned in the article will also be given in the form of linear matrix inequalities (LMI). Finally, a numerical example is given, which takes two uncertain values respectively and solves the output feedback controller's parameters by the theorem proposed in the paper. According to the required controller parameter values, the validity of the theorem proposed in the article is compared and verified by simulation. [ABSTRACT FROM AUTHOR]

Featured Application: Presented filtering structure can be used to improve the operation and dynamics of filters. This paper presents a concept of the non-stationary filtering network with reduced transient response consisting of the first-order digital elements with time-varying parameters. The digital filter section is based on the analog system. In order to design the filtering network, the analog prototype was subjected to the discretization process. The time constant and the gain factor were then temporarily varied in time in order to suppress the transient response of the designed filtering structure. The optimization method, based on the Particle Swarm Optimization (PSO) algorithm which is aimed at reducing the settling time by a proper parameter manipulation, is presented. Simulation results proving the usefulness of the proposed concept are also shown and discussed. [ABSTRACT FROM AUTHOR]

The problem of l2-l∞ stability and disturbance attenuation performance analysis of fixed-point state-space digital filters with external disturbance and finite wordlength nonlinearities is studied in this paper. The finite wordlength nonlinearities are composite nonlinearities representing concatenations of quantization and overflow correction employed in practice. Using sector-based characterization of the finite wordlength nonlinearities, a new l2-l∞ stability criterion for the reduction of the effects of external disturbance to a given level and to confirm the nonexistence of limit cycles in the absence of external interference is established. Numerical examples are given to illustrate the efficacy of the proposed criterion. [ABSTRACT FROM AUTHOR]

This paper presents a technique to estimate the coefficients of a multiple-look-up table (LUT) digital predistortion (DPD) architecture based on the partial least-squares (PLS) regression method. The proposed 3-D distributed memory LUT architecture is suitable for efficient FPGA implementation and compensates for the distortion arising in concurrent dual-band envelope tracking power amplifiers. On the one hand, a new variant of the orthogonal matching pursuit algorithm is proposed to properly select only the best LUTs of the DPD function in the forward path, and thus reduce the number of required coefficients. On the other hand, the PLS regression method is proposed to address both the regularization problem of the coefficient estimation and, at the same time, reducing the number of coefficients to be estimated in the DPD feedback identification path. Moreover, by exploiting the orthogonality of the PLS transformed matrix, the computational complexity of the parameters’ identification can be significantly simplified. Experimental results will prove how it is possible to reduce the DPD complexity (i.e., the number of coefficients) in both the forward and feedback paths while meeting the targeted linearity levels. [ABSTRACT FROM AUTHOR]

This paper presents a novel learning control method for ball-screw-driven stages. In recent years, many types of friction models that are based on complicated equations have been studied. However, it is difficult to treat friction models with equations because the level of precision that is associated with real friction characteristics and parameter tuning are difficult to achieve. In contrast, repetitive perfect tracking control (RPTC) is a repetitive control technique that achieves high-precision positioning. In this paper, we propose the use of RPTC with n-times learning filter. The n-times learning filter has a sharper rolloff property than conventional learning filters. With the use of the n-times learning filter, the proposed RPTC can converge tracking errors n times faster than the RPTC with the conventional learning filter. Simulations and experiments with a ball-screw-driven stage show the fast convergence of the proposed RPTC. Finally, the proposed learning control scheme is combined with data-based friction compensation, and the effectiveness of this combination is verified for the x–y stage of a numerically controlled machine tool. [ABSTRACT FROM PUBLISHER]

This paper presents a pattern recognition-based scheme for detection of islanding conditions in synchronous- based distributed generation (DG) systems. The main idea behind the proposed scheme is the use of spatial features of system parameters such as the frequency, magnitude of positive sequence voltage, etc. In this study, the system parameters sampled at the point of common coupling (PCC) were analyzed using reduced-noise morphological gradient (RNMG) tool, first. Then, the spatial features of the RNMG magnitudes were calculated. Next, to optimize and increase the ability of the proposed scheme for islanding detection, the best features with a much discriminating power were selected based on separability index (SI) calculation. Finally, to distinguish the islanding conditions from the other normal operation conditions, a support vector machine (SVM) classifier was trained based on the selected features. To investigate the power of the proposed scheme for islanding detection, the results of examinations on the various islanding conditions including system loading and grid operating state were presented. These results show that the proposed algorithm reliably detect the islanding condition within 32.7 ms. [ABSTRACT FROM AUTHOR]

We analyze the propagation properties of the numerical versions of one- and two-dimensional wave equations, semi-discretized in space by finite difference schemes. We focus on high-frequency solutions whose propagation can be described, both at the continuous and at the semi-discrete levels, by micro-local tools. We consider uniform and non-uniform numerical grids as well as constant and variable coefficients. The energy of continuous and semi-discrete high-frequency solutions propagates along bi-characteristic rays, but their dynamics are different in the continuous and the semi-discrete setting, because of the nature of the corresponding Hamiltonians. One of the main objectives of this paper is to illustrate through accurate numerical simulations that, in agreement with micro-local theory, numerical high-frequency solutions can bend in an unexpected manner, as a result of the accumulation of the local effects introduced by the heterogeneity of the numerical grid. These effects are enhanced in the multi-dimensional case where the interaction and combination of such behaviors in the various space directions may produce, for instance, the rodeo effect, i.e., waves that are trapped by the numerical grid in closed loops, without ever getting to the exterior boundary. Our analysis allows to explain all such pathological behaviors. Moreover, the discussion in this paper also contributes to the existing theory about the necessity of filtering high-frequency numerical components when dealing with control and inversion problems for waves, which is based very much on the theory of rays and, in particular, on the fact that they can be observed when reaching the exterior boundary of the domain, a key property that can be lost through numerical discretization. [ABSTRACT FROM AUTHOR]

In this paper, a novel pulse interference filter for fiber Bragg grating (FBG) interrogation based on the tunable Fabry-Perot (F-P) filtering principle is proposed and experimentally demonstrated. The self-developed FBG interrogation system is devised for the aircraft health management of key structures. Nevertheless, the pulse interference is detected in the reflection spectrum of FBG causing interrogation system unstable. To address the problem, the first-order lag pulse broadening filter is proposed in this paper. The first-order lag filter is applied to preprocess and smooth the original signal, meanwhile enhancing the signal-to-noise ratio (SNR). Afterwards, peaks of reflection spectrum are distinguished with pulse interference by pulse broadening. Experimental results indicate that 634 peaks are detected before adopting the first-order lag pulse broadening filter. Comparatively, the number of peaks decreases to 203 after filtering the interference pulse, and the correct rate of peak detection is higher than 98.5%. Through the comparison with the finite impulse response (FIR) filter, the advantage of first-order lag filter is proved. The vibration monitoring experiment demonstrates that this system has high dynamic precision with a dynamic interrogation range of 0 Hz-400 Hz, and the maximum repetition rate of 800 Hz. [ABSTRACT FROM AUTHOR]

Modeling for an unknown plant is a very important and primary task in the control system engineering. By using this established model, an adequate controller can be further designed to meet certain control specifications. This paper will propose a new modeling method which is based on the infinite impulse response (IIR) digital filter structure. A modified particle swarm optimization (PSO) with multiple subpopulations is utilized to solve for the IIR filter coefficients to model an unknown digital system. The developed PSO algorithm is able to overcome the multimodal error surface problem that often occurs in the system modeling of IIR digital filter. Finally, three different kinds of digital systems are examined to demonstrate the feasibility of the proposed method, including the same system order and reduced order structures. It is concluded from several simulation results that the proposed method has an excellent performance on solving the IIR digital modeling problem. [ABSTRACT FROM AUTHOR]

Widely linear (WL) receivers have the capability to perform single antenna interference cancellation (SAIC) of one rectilinear (R) or quasi-rectilinear (QR) co-channel interference (CCI), a function which is operational in global system for mobile communications (GSM) handsets in particular. Moreover, SAIC technology for QR signals is still required for voice services over adaptive multiuser channels on one slot (VAMOS) standard, a recent evolution of both GSM and enhanced data rates for GSM evolution (EDGE) standards, to mitigate legacy GSM CCI in particular. It is also required for filter bank multicarrier offset quadrature amplitude modulation (FBMC-OQAM) networks, which are candidate for 5G mobile networks, to mitigate intercarrier interference at reception for frequency selective propagation channels in particular. In this context, the purpose of this paper is twofold. The first one is to get more insights into the existing SAIC technology, and its extension to multiple antenna called multiple antenna interference cancellation (MAIC), by showing analytically that, contrary to what is accepted as true in the literature, SAIC/MAIC implemented from standard WL filtering may be less efficient for QR signals than for R ones. From this result, the second purpose of the paper is to propose and to analyze, forQRsignals and frequency selective fading channels, an SAIC/MAIC enhancement based on a three-input WL frequency shift receiver, making QR signals always almost equivalent to R ones for WL filtering in the presence of CCI. The results of the paper, completely new, may contribute to develop elsewhere new powerful WL receivers for QR signals and for both VAMOS and FBMC-OQAM networks in particular. [ABSTRACT FROM AUTHOR]

Most existing phasor measurement units (PMUs) are noncausal PMUs and they compensate for the group delay in PMU applications by shifting time stamps, which may result in high latency that will impair performance of PMU applications. This paper presents causal PMUs to reduce the group delay caused latency without shifting time stamps, and studies the impact of causality on performance of PMU algorithms. The paper first analyzes how causal and noncausal PMUs compensate for the group delay caused by digital filters and it is found that causal PMUs normally reduce latency by the group delay, whereas noncausal PMU will not. Then, the impact of causality on performance of PMU algorithms is investigated and analyzed by using the Hydro Quebec Research Institute (IREQ) PMU model and the IEEE PMU model. Finally, the simulation results carried out on two test systems highlight the difference between the causal method and the noncausal method under fault conditions in realistic multimachine setups. [ABSTRACT FROM AUTHOR]

Servo-hydraulic actuators exhibit frequency-dependent variations of amplitude and delay during real-time hybrid simulation (RTHS). Effective compensation techniques to overcome these variations is a crucial component for the successful implementation of RTHS. Most of the existing compensation techniques have demonstrated effective performance under excitations with relatively low frequency bandwidth. To further advance the servo-hydraulic compensation for broader frequency bandwidth, this paper presents the design and performance evaluation of an optimal discrete-time model-based feedforward controller under inputs with broader frequency bandwidth as high as 0–30 Hz. As a compensation technique has not been fully explored in RTHS, the model-based design of discrete-time domain compensation techniques introduces the new technical challenge of inverting nonminimum phase systems. This paper identifies this new challenge by providing detailed supporting derivation, and explains the use of a digital filtering technique—a finite impulse response (FIR) filter—to address this new challenge, and the development process of the proposed FIR compensator using different optimization schemes. Furthermore, this paper demonstrates the compensation performance of the proposed FIR compensator, both numerically and experimentally, under reference inputs with various bandwidths, including bandlimited white noises with frequency bandwidth as high as 0–30 Hz. For comparison purposes, several existing feedforward compensation techniques are also implemented and compared with the proposed FIR compensator. Based on this study, it is found that the proposed FIR compensator technique not only provides excellent compensation performance under various bandwidths, but also offers great flexibility in its formulation by varying the model order with desired compensation performance and computational demands. [ABSTRACT FROM AUTHOR]

The maximally flat variable-delay (VD) digital filter can be derived by using the discrete-Pascal-transform (DPT) and the DPT-based Pascal-polynomial interpolation. In this paper, we develop an efficient structure for the low-complexity and high-modularity implementation of this Pascal-type VD filter. As compared to other existing filter structures, this new structure greatly reduces the multiplication operations required in the filtering process. Roughly speaking, the proposed new structure can reduce the multiplication operations by almost one-third. Thus, this new filter structure has the lowest filter complexity among all the existing filter structures for the implementation of the maximally flat VD filter. As a result, signal interpolation can be efficiently performed through utilizing this new filter structure. As opposed to other existing structure with transient problem, we will show that the proposed new structure does not involve any transient problem. That is, it is a transient-free structure. Consequently, the proposed new filter structure can achieve more accurate signal-interpolation results than other structures that have the transient problem. Finally, we show that this proposed structure also has high modularity and it is suited for modularized hardware implementation. [ABSTRACT FROM PUBLISHER]

The full-cycle discrete Fourier transform (FCDFT) is commonly used to estimate phasors in numerical relays because of its immunity to harmonics and accurate identification of a decaying dc component (DDC) in a fault current. For fast protection of power systems, it is necessary to speed up the phasor estimation by using a data window below one cycle. The conventional least squares (LS) methods below one cycle approximate the DDC as the first several terms of the Taylor series expansion, which degrades the phasor-estimation accuracy. This paper proposes an LS method that uses Fourier analysis for approximation of the DDC to speed up phasor estimation without accuracy degradation. The phasor-estimation accuracy of the proposed method is investigated for the data-window length in simulations using synthetic data of fault currents containing DDC, harmonics, and measurement noise. The phasor-estimation speed is also investigated with respect to the delay of the antialiasing filter in the numerical relay. The proposed method is compared with the conventional LS and FCDFT methods in simulations using synthetic fault-current data. The feasibility of the proposed method is demonstrated through the phasor estimation of simulated transmission-line faults. [ABSTRACT FROM AUTHOR]

High-dimensional high-frequency continuous-vibration control problems often have very complex dynamic behaviors. It is difficult for the conventional control methods to obtain appropriate control laws from such complex systems to suppress the vibration. This paper proposes a new vibration controller by using reinforcement learning (RL) and a finite-impulse-response (FIR) filter. First, a simulator with enough physical fidelity was built for the vibration system. Then, the deep deterministic policy gradient (DDPG) algorithm interacted with the simulator to find a near-optimal control policy to meet the specified goals. Finally, the control policy, represented as a neural network, was run directly on a controller in real-world experiments with high-dimensional and high-frequency dynamics. The simulation results show that the maximum peak values of the power-spectrum-density (PSD) curves at specific frequencies can be reduced by over 63%. The experimental results show that the peak values of the PSD curves at specific frequencies were reduced by more than 47% (maximum over 52%). The numerical and experimental results indicate that the proposed controller can significantly attenuate various vibrations within the range from 50 Hz to 60 Hz. [ABSTRACT FROM AUTHOR]

Filter design in signal processing field plays a vital role in achieving low power dissipation, which is essential for portable gadgets. This paper proposes an effective flexible FIR filter structure, which is adaptive and utilizes multiply-accumulate (MAC) core. Most common algorithm for filter coefficient optimization includes least mean square (LMS) and recursive least square (RLS). Though the performance of the recursive least square (RLS) algorithm is superior as compared to the least mean square (LMS); because of higher arithmetic complexity in design, it has not been preferred for real time applications. The fundamental filter has used a LMS based tapped delay line filter, which is practically a feasible choice for adaptive filtering algorithm in order to attain lesser computation. In the proposed work, the adjustable coefficient filters using an optimized LMS approach has been implemented for the utilization of determining the unexplored system. The filter tap considered here is a 32-tap and its analysis and synthesis has been carried out using hardware description language (HDL) programming and synthesized in field programmable gate array (FPGA) devices. The placement and post routing design has offered good performance in terms of utilized resources. The implemented filter architecture requires 80% reduction in resources and has enhanced the clock frequency by about five times when examined with the reported architecture. [ABSTRACT FROM AUTHOR]

This paper briefly studies the method of collecting audio signals and the method of adding noise to audio signals. It comprehensively applies various basic knowledge of digital signal processing, and then performs spectrum analysis on noise-free frequency signals and spectral analysis of noise-added frequency signals, and filtering processing. Through theoretical derivation, the corresponding conclusions are drawn, and then MATLAB is used as a programming tool to carry out computer implementation to verify the conclusions derived. In the research process, the filter processing was completed by designing the IIR digital filter and the FIR digital filter, and MATLAB was used to draw the graphics and calculate and simulate some data in the whole design. [ABSTRACT FROM AUTHOR]

The volume hologram printer is useful for 3D display, because it is selective to the wavelength and be able to reconstruct with the natural illumination. There are many studies of a volume hologram printer been studied to output a volume hologram from a computer-generated hologram. The final volume hologram consists of tiled small holograms and the tiling manner often causes spilt lines which will have impact on image quality. With an intent to get rid of the split lines and improve the quality, fully overlapping printing was proposed recently. Each elemental hologram is overlapped both in vertical and horizontal directions by 50%. Then, the hologram is printed four times in each area and it makes the printing speed four times slower. For this case, partially overlapping printing is proposed in this paper to improve image quality with small effect in printing speed. For partial overlapping, a digital spatial filter is projected and added to every elemental hologram. Using the digital spatial filter, different partially overlapped holograms are calculated and reconstructed to compare to the non-overlapped ones. The simulation result shows that the overlapped one (10% in both vertical and horizontal) has much weaker gaps and black lines. [ABSTRACT FROM AUTHOR]

In this paper we target the Fixed-Point (FxP) implementation of Linear Time-Invariant (LTI) filters evaluated with state-space equations. We assume that wordlengths are fixed and that our goal is to determine binary point positions that guarantee the absence of overflows while maximizing accuracy. We provide a model for the worst-case error analysis of FxP filters that gives tight bounds on the output error. Then we develop an algorithm for the determination of binary point positions that takes rounding errors and their amplification fully into account. The proposed techniques are rigorous, i.e., based on proofs, and no simulations are ever used. In practice, Floating-Point (FP) errors that occur in the implementation of FxP design routines can lead to overestimation/underestimation of resulting parameters. Thus, along with FxP analysis of digital filters, we provide FP analysis of our filter design algorithms. In particular, the core measure in our approach, Worst-Case Peak Gain, is defined as an infinite sum and has matrix powers in it. We provide fine-grained FP error analysis of its evaluation and develop multiple precision algorithms that dynamically adapt their internal precision to satisfy an a priori absolute error bound. Our techniques on multiple precision matrix algorithms, such as eigendecomposition, are of independent interest as a contribution to Computer Arithmetic. All algorithms are implemented as C libraries, integrated into an open-source filter code generator and tested on numerical examples. [ABSTRACT FROM AUTHOR]

In this paper, a new method is presented for the design of a low pass filter (LPF) based on an LC equivalent circuit. Firstly, new formulas are proposed to calculate an LC equivalent circuit of a rhombus-shaped resonator. Secondly, the transfer function and transmission zero of the rhombus-shaped resonator are extracted, based on the presented formulas. Then other rhombus-shaped resonators are designed, based on the extracted formulas. The proposed filter has a cut-off frequency with an attenuation level of 3 dB at 1.54 GHz. The obtained return loss and insertion loss in the pass band are 16 dB and 0.1 dB, respectively. The designed filter is fabricated on RT-5880 with 31 mil thickness. [ABSTRACT FROM AUTHOR]

A new class of cascade digital orthogonal filters of the Malmquist type based on bilinear transformation for mapping poles to zeroes and vice versa is presented in this paper. In a way, it is a generalization of the majority of the classical orthogonal filters and some newly designed filters as well. These filters are orthogonal with respect to the generalized inner product which is actually a generalization of the classical inner product. Outputs of these filters are obtained by using polynomials orthogonal with respect to the new inner product. The main quality of these filters is that they are parametric adaptive. The filter with six sections is practically realized in the Laboratory for Modeling, Simulation and Control Systems. Performances of the designed filter are proved on modeling and identification of the system for differential pulse code modulation. Real response and response from the proposed filter are compared with regard to the chosen criteria function. Also, a comparative analysis of the proposed filter with some existing filters is performed. [ABSTRACT FROM AUTHOR]

The current version of the data over cable service interface specification (DOCSIS), which is DOCSIS 3.1, is markedly different from previous versions in that orthogonal frequency-division multiplexing (OFDM) is used together with high-density QAM constellations (up to 4096-QAM) in both the downstream and upstream directions to facilitate high data rates. This is in a sharp contrast with the single-carrier modulation techniques used in prior versions of DOCSIS. Despite many advantages, a drawback of OFDM is the insertion of a cyclic prefix (CP) at the beginning of each transmitted OFDM symbol to mitigate inter-symbol interference (ISI). The CP, which is configurable, but can be as large as 25% of the symbol time for DOCSIS 3.1 downstream transmission, does not carry useful data and therefore reduces the overall transmission throughput. In general, not only the channel but also the transceivers’ digital filters determine the ISI and therefore the length of the CP. In this paper, the aspects that determine the CP length are thoroughly addressed. A novel technique to eliminate the CP is introduced and analyzed. It is demonstrated that the CP can be completely removed with a negligible effect on the transmission performance using this technique. Moreover, the proposed technique requires only a modest amount of hardware, making it a promising candidate to be included in the a future version of DOCSIS. [ABSTRACT FROM AUTHOR]

The Laplace operator is a differential operator which is used to detect edges of objects in digital images. This paper presents the properties of the most commonly used third-order 3>3 pixels Laplace contour filters including the difference schemes used to derive them. The authors focused on the mathematical properties of the Laplace filters. The basic reasons of the differences of the properties were studied and indicated using their transfer functions and modified differential equations. The relations between the transfer function for the differential Laplace operator and its difference operators were described and presented graphically. The impact of the corner elements of the masks on the results was discussed. This is a theoretical work. The basic research conducted here refers to a few practical examples which are illustrations of the derived conclusions. We are aware that unambiguous and even categorical final statements as well as indication of areas of the results application always require numerous experiments and frequent dissemination of the results. Therefore, we present only a concise procedure of determination of the mathematical properties of the Laplace contour filters matrices. In the next paper we shall present the spectral characteristic of the fifth order filters of the Laplace type. [ABSTRACT FROM AUTHOR]

In rotor-slot-harmonic-based speed detection schemes, a grid-connected induction motor's rotational speed isresolved from the phase of a rotor slot harmonic signal for condition monitoring purposes. In such schemes,frequency-selective digital filters are often applied to attenuate interferences in sampled motor currents before rotorslot harmonic signals are extracted. This paper demonstrates that the use of linear-phase filters, which is a family ofdigital filters with linear phase responses, helps preserve the rotor slot harmonic signal's phase during the filteringoperation. This paper also shows that, for grid-connected induction motors with periodically time-varying loads, therotor slot harmonic signal's frequency is modulated by periodic speed oscillations and hence contains multiple sidebandsin the frequency spectrum. Experimental results further show that linear-phase filters allow for a more accuratedetection of the induction motor speed than filters with nonlinear phase responses. [ABSTRACT FROM AUTHOR]

In resistance-based rotor temperature estimation schemes, a grid-connected induction motor's rotor temperature is derived from a resistance quantity based on an equivalent circuit model. This temperature is susceptible to fluctuations in the motor's supply frequency. In this paper, the relationship between supply frequency fluctuations and accuracy in resistance-based rotor temperature estimates is analyzed, and a complex adaptive phase discriminator is proposed to track the supply frequency fluctuations for grid-connected induction motors. A complex voltage vector is constructed from polyphase voltage measurements and passed through a frequency-selective digital filter to attenuate harmonics and interference. The complex adaptive phase discriminator then operates on the filtered voltage signal, iteratively adapting a complex reference signal's phase to align it with the filtered voltage signal. The power grid's supply frequency is directly estimated from the adapted phase on a sample-by-sample basis. Experimental results demonstrate that the proposed complex adaptive phase discriminator helps produce rotor temperature estimates with increased accuracy. [ABSTRACT FROM AUTHOR]

Guaranteeing the stability is one of the most critical issues in designing a variable recursive digital filter. In this paper, we first present an odd-order recursive variable model (transfer function) that is used for designing an odd-order variable-magnitude (VM) digital filter, and then we replace the original coefficients of the denominator of the odd-order transfer function with a set of new parameters. These new parameters can ensure that they can take arbitrary values without incurring instability of the designed odd-order VM filter. To make the VM filter coefficients variable, we find all the VM filter coefficients as polynomial functions of the tuning parameter, which includes two phases. The first phase designs a set of recursive digital filters with fixed coefficients (constant filters), and the second phase utilizes a curve-fitting scheme to represent each coefficient as a polynomial function. As a result, the VM filter coefficients become variable, and the proposed parameter-substitution-based denominator coefficients ensure the filter stability. This is the most important contribution of the parameter-substitution-based design scheme. This paper uses the fifth-order demonstrative example to verify the stability guarantee as well as the design accuracy of the obtained the fifth-order VM filter. [ABSTRACT FROM AUTHOR]