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This work proposes an efficient analytic method for designing a class of 2D filters useful in image processing, namely wedge-shaped filters, which can be considered components of a directional filter bank. The design starts from a 1D digital filter prototype transfer function. Using accurate approximations and specific frequency mappings, first an unilateral, half-plane filter with a given orientation is obtained. Using two such unilateral 2D filters with imposed orientation angles, a desired directional wedge filter is derived, with specified orientation and aperture angles. Its transfer function results directly in a factored form, which is an advantage in implementation. The resulted wedge filter is parametric and tunable, since the specified parameters occur in the final matrix form of the filter transfer function.

Digital systems are placed at the core of information technology and they are used extensively in electronics. The digital filter realization has become a central topic of signal processing studies. This paper presents a discrete IIR filter design method for approximate realization of fractional order continuous filters in digital systems. For this purpose, Fractional Order Darwinian Particle Swarm Optimization (FODPSO) method is modified to provide better fitting of a discrete IIR filter function to a fractional order continuous filter and we implemented a hybrid version of FODPSO method, where the initial particle generation is carried out by arithmetical candidate point selection technique of the Base Optimization Algorithm (BaOA). This modification expands the search range of the FODPSO and thus the optimized discrete IIR filter can provide better approximation to amplitude response of fractional order continuous filter functions. In the paper, several illustrative examples are presented to demonstrate the performance of proposed methods. (C) 2017 Elsevier Ltd. All rights reserved.

Digital filters are now key components in many modern digital systems. This paper proposed a novel evolutionary method to design structure-diversified digital filters. On the investigation of the existing evolution-based digital filter design methods, most state-of-the-art works concentrate on the evolution of appropriate transfer functions for digital filters. However, a transfer function is not equivalent to a practical digital filter that has proper structure and can be implemented by a hardware directly. Some researchers proposed a synthesis method to generate the structure of digital filter from a specified transfer function. However, this method needs an existing transfer function as the prior knowledge. Compared with existing works on the evolution of digital filters, the proposed method is novel at the following aspect: the proposed method can directly evolve the structure and parameters of digital filter without the pre-definition of the transfer function. The only prior knowledge we need is the specification of the design target, such as the frequency range of the passband and stop-band. In the experimental study, a significant characteristic is revealed that the proposed method is able to evolve structure-diversified filters with approximate frequency response. The proposed method is a prototype, and it is demonstrated to be a promising way of digital filter design.

This paper proposes two new recursive filtering structures based on the nonlinear myriad operator. First, we develop the general class of recursive weighted myriad (RWMy) filters as a robust filtering structure against impulsive noise that includes, as particular cases, a normalized version of the linear infinite impulse response (IIR) filter, the recursive mode-type filter, and the non-recursive weighted myriad filter. Secondly, considering the fact that the additive noise that contaminates the previous filter's outputs is no longer impulsive, we introduce a novel class of recursive hybrid myriad (RHMy) filters whose structure gathers the advantages of both the weighted myriad and the weighted mean in a single cost function to be minimized. Some properties of the RHMy filter are derived and a fast algorithm to compute the RHMy filter output is proposed. Furthermore, adaptive algorithms for designing the proposed recursive structures, under the equation error formulation framework, are developed. Finally, extensive numerical simulations are shown to evaluate both the iterative update of the adaptive algorithms and the performance of the proposed recursive filters against impulsive noise.

Linear phase is an important characteristic of digital filters in many signal processing applications. In this paper, two iterative reweighted minimax phase error algorithms are proposed to design nearly linear-phase infinite impulse response (IIR) digital filters with prescribed or simultaneously minimized magnitude errors and preset transition-band gain. In each iteration of the algorithms, a weighted minimax phase error problem with a fixed weight function is firstly solved using a modified Gauss-Newton method with a variable step length, and the weight function of the phase error is then updated using the square root of a modified envelope of the group-delay error of the filter. With the proposed methods, both very small phase error and group-delay error have been obtained while meeting the requirements on the passband and stopband magnitude errors and the transition-band gain. Design examples demonstrate the effectiveness of the proposed methods and the excellent performance of the designed filters.

This paper presents the design method for Infinite Impulse Response (IIR) digital filter with the use of Real Coded Genetic Algorithm (RGA/RCGA). Generally, nonlinear and multimodal error surface is observed in case of digital IIR filter. Hence, to avoid problems such as local minima, global optimization techniques are required. This paper gives effective method to design digital IIR filters. This paper finds the optimum coefficients of IIR digital filter by using RGA. RGA works on real numbers and is a powerful global optimization algorithm. To obtain minimum transition band, this designing of low pass IIR digital filter is proposed. It is observed that the calculated values are more optimal than those which are obtained by FDA tool available for design of filter in MATLAB. The improved mean-square-error (MSE) is observed in simulation results for example taken. General Terms Digital filter design, optimization algorithm, Frequency response, filter coefficients

This paper presents a technique to estimate the temperature of each power electronic device in a thermally coupled, multiple device system subject to dynamic cooling. Using a demonstrator system, the thermal transfer impedance between pairs of devices is determined in the frequency domain for a quantized range of active cooling levels using a technique based on pseudorandom binary sequences. The technique is illustrated by an application to the case temperatures of power devices. For each cooling level and pair of devices, a sixth-order digital IIR filter is produced, which can be used to directly estimate temperature from device input power. When the cooling level changes, the filters in use are substituted and the internal states of the old filters are converted for use in the new filter. Two methods for filter state conversion are developed—a computationally efficient method, which is suited to infrequent changes in power dissipation and cooling, and a more accurate method, which requires increased memory and processing capacity. Results show that the temperature can be estimated with low error using a system which is suitable for integration on an embedded processor.

This paper proposes an integrated optimization technique which combines the features of the cat swarm optimization (CSO) algorithm with the traditional differential evolution (DE) algorithm and applies it for the optimal design of digital infinite impulse response (IIR) filters. Traditional design methods treat the digital IIR filter design as a single-objective optimization problem by taking into account the minimization of magnitude response error only and lack in considering the linear phase response error and the order of the filter. The aim of this paper was to design an IIR filter in multi-objective framework by equally considering the minimization of magnitude response error, the linear phase response error and the order of the filter. Firstly, the CSO algorithm is applied for digital IIR filter design. In order to start with a better solution set, the opposition-based learning strategy is then incorporated. To further improve the performance of CSO for designing stable digital IIR filters, the DE optimization algorithm is combined with CSO hence producing an integrated algorithm called multi-objective cat swarm and differential evolution algorithm (MOCSO-DE) which has the capability to explore and exploit the solution search space locally as well as globally. The developed integrated algorithm is effectively applied for the designing of the digital IIR low-pass (LP), high-pass (HP), band-pass (BP) and band-stop (BS) filters. To evaluate the effectiveness of the developed integrated algorithm, the computational results are compared with some well-established algorithms and it is observed that the developed algorithm is superior or at least comparable to other algorithms in getting better magnitude response and linear phase response together with lowest filter order and can also be implemented for the higher-order filter designs.

Adaptive infinite impulse response (IIR) filter has been preferably used in modeling real-world systems because of its reduced number of coefficients and better performance over finite impulse response (FIR) filter. However, it is still a challenging problem how to design an optimal IIR filter due to its nonlinear and multimodal error surface. This paper introduces membrane computing to design an optimal IIR filter and proposes a novel design method that employs a tissue-like membrane system with ring-shaped topology structure. A modification of the different evolution mechanism was developed as evolution rules for objects according to the special membrane structure. Under the control of the object's evolution-communication mechanism, the tissue-like membrane system can effectively find the global minima for an IIR filter design problem. The proposed method was evaluated over several benchmark IIR systems and was compared with several state-of-the-art evolutionary algorithms. The experimental results show that the proposed method has better identification performance compared with other algorithms.

The paper deals with method of designing of a digital equalizer for analog signal path with ADC and low-order low-pass filter on its front. The correction effect is achieved through use of the IIR digital filters, designed in equalization purposes of the magnitude frequency response. The application of an equalizer allows to gain high attenuation in cutoff band and expand the signal bandwidth. Simultaneously it allows using low order anti-aliasing analog filter on ADC front. The equalizer can operate as a separate device or could be build-in signal processor (or in any other signal processing ASIC). In the first case it could be prepared as a module, implemented in FPGA device.

This paper presents an analytic design technique for 2D IIR filters with elliptical symmetry, which have useful applications in image processing. The design is based on efficient elliptic digital filters, regarded as 1D prototypes, to which specific complex frequency transformations are applied; this allows to obtain directly a factored form of the transfer function for the 2D elliptically-shaped filter. The design procedure uses accurate approximations, but no global optimization algorithm. Finally the 2D filter matrices are obtained. The filter is adjustable, its coefficients depending explicitly on the specified orientation and bandwidth. Another advantage is versatility, since the design need not be resumed each time from the start for various specifications. The designed 2D filters have an accurate elliptical shape with low distortions even close to the frequency plane margins, being efficient, of high selectivity and low order.

There are two major types of digital filters in terms of structure: infinite impulse response (IIR) and finite impulse response (FIR). Digital IIR filters often provide a much better performance and less computational cost than FIR filters and have become the target of growing interest. Since the problem of the error surface of designing digital IIR filters is generally nonlinear and multimodal, global optimization techniques are required in order to avoid local minima. In this paper, an evolutionary method has been proposed to design digital IIR filters. This method is based on Imperialist Competitive Algorithm (ICA) and by adding a step to the existing steps of ICA, performance of it has been improved in searching solution space and convergence to the global minima. Obtained results from simulation using proposed method and other algorithms show that the proposed method is suitable for designing digital IIR filter.

IIR implementation of filters exhibiting critical monotonic amplitude characteristic (CMAC) in the pass-band is introduced for the first time. After short description of the CMAC filters in the s -domain and discussion of the choice between FIR and IIR filters, IIR filters will be adopted and the bilinear transform will be chosen for transformation of the analog into digital transfer functions. Parallel realization of the IIR filter will be enabled by proper preparation of the analog data. The influence of the truncated coefficients will be considered and its effects will be demonstrated by an example proving the robustness of the transformed function. A design procedure will be proposed for the CMAC filter functions with arbitrary maximum pass-band attenuation.

A new greedy search method is applied in this paper to design the optimal digital infinite impulse response (IIR) filter. The greedy search method is based on binary successive approximation (BSA) and evolutionary search (ES). The suggested greedy search method optimizes the magnitude response and the phase response simultaneously and also finds the lowest order of the filter. The order of the filter is controlled by a control gene whose value is also optimized along with the filter coefficients to obtain optimum order of designed IIR filter. The stability constraints of IIR filter are taken care of during the design procedure. To determine the trade-off relationship between conflicting objectives in the non-inferior domain, the weighting method is exploited. The proposed approach is effectively applied to solve the multiobjective optimization problems of designing the digital low-pass (LP), high-pass (HP), bandpass (BP), and bandstop (BS) filters. It has been demonstrated that this technique not only fulfills all types of filter performance requirements, but also the lowest order of the filter can be found. The computational experiments show that the proposed approach gives better digital IIR filters than the existing evolutionary algorithm (EA) based methods.

The proposed research work on the topic Infinite Impulse Response "IIR Structure and Its Application" is basically state space representation for the digital filter of different form obtained from analog filter and transformation to digital one. In the normal course of analysis the digital filter transfer function are realized in different forms using time delay elements and multipliers. This realization can be eased if digital filter are represented in state space techniques opening a new field for computation analysis. This aspect has been incorporated in the proposed research work things outlining the introduction of IIR filter and different structure including ladder and wave structure realization, state space description of IIR filter is presented in detail including the normal form which has complex structure but simple form of state equation. IIR filter design is based on state space technique using Lattice structure. The generalized technique of state space equation realized from general form of digital filter transfer function has been developed then the technique is demonstrated using differential form of various filter like LPF, HPF and BPF for the required order of analog filters. Statistical analysis of digital filter like round off error and dynamic scaling has been incorporated, where the two direct computes have been lumped together in the common state space representation. Autocorrelation and uncorrelation between noise and input samples gives round off noise and dynamic scaling give expression for the factor forms, round off error and dynamic range. This aspect on statistical analysis of digital filter has opened a new field for research.

In some measurement applications, it is required to have digital filters which simultaneously possess a constant group delay in the passband and a narrow transition band. This kind of filters is usually implemented using allpass filter section which compensates the unfavorable run of the group delay response of the original filter. Unfortunately, the process of equalisation affects the time domain characteristics of the (whole) equalised system. This paper presents theoretical concept and simulation results of a new class of low-pass time-varying infinite impulse response (IIR) filters with equalised group delay response and a transient response of short duration. The improvement of the filters in the time domain is achieved by means of temporary change in the value of the filter parameters. Computer simulations verifying the effectiveness of the proposed IIR filters with equalised group delay response and reduced transient response are presented and compared to the performance of traditional filters.

In this brief, a fast design technique based on a multiband mapping relation is discussed for infinite-impulse-response digital filters with a general Chebyshev characteristic, which is suitable for single- and multiband operations. Each bandwidth and the ripple in it can be accurately controlled. Without increasing the order of the filters, the out-of-band performance of the filters can be easily adjusted by appropriately placing transmission zeros wherever they are desired. In addition, complex transmission zeros can also be introduced to improve the group delay to some extent. The proposed technique is analytical and easy to implement.

In order to attenuate the added noise by electric network used by myoelectric signals acquisition equipment, in this research work, it is developed an IIR digital filter implemented on FPGA. This filter removes a specific spectra frequencies without adding noise to the signal, which allows a better performance in the usage that is given to the signals. The filter coefficients are taken and proved from MATLAB functions. Then, those are transferred to the filter design in the FPGA. For this purpose, it was used a Basys 3 of Xilinx Artix-7 family and the design was implemented in Vivado Design Suite. The filtered signal does not present additional noise and it was eliminated the desired frequency.

A relatively recent innovation in the domain of digital filtering has been the introduction of signal processing applications with effective power utilization. No scope towards the effective and efficient architecture realization with existing part of literature, and hence investigation is made and is confined with cascade form of filter design. In this paper, architectures are realized based on common set of specifications to arrive at the high performance recursive filter for low power applications using Xilinx System Generator. Infinite Impulse Response (IIR) filters can be realized in many forms those are Direct form-I, Direct form-II, Cascade, parallel form. All these structures provide a space for selection of an appropriate architecture for reduction of power consumption and improvement in speed of digital filters. In this particular work, a 5th order low pass IIR filter is realized in Direct form-I, Direct form-II, Cascade form (Direct form-I/ Direct form-II) as an example of the methodology in a Xilinx FPGA device. Also corresponding power analysis was performed and finally concluded that cascade (Direct form-I) realization is the best technique to implement higher order IIR filters when power is a main constraint, cascade (Direct form-II) technique is best with area and speed as constraints.

The evolution of multi-feature portable devices with high speed processors and with drastic growth in component density turns the designer attention towards power aware design schemes. In low power VLSI designs an adaptive filter can obtain a reduction in terms of area and power consumption. A system with a linear transfer function controlled by variable parameters and a means to adjust those parameters according to an optimization algorithm is called adaptive filter. The Least Mean Square (LMS) filter is one of adaptive filters type which is used commonly, because of its simplicity and also because of its satisfactory convergence performance. The current IIR adaptive filter uses LMS to reduce area-delay product and energy-delay product. To reduce this delay one can implement filter in pipelined structure. Shift-add tree efficiently minimizes the critical path and silicon area without increasing the number of adaptation delays. The structure of IIR adaptive filter designing is done by using two main blocks: IIR block and new coefficients block (weights block). Weights block consists of series of partial product generators and shift/add tree. Partial product generators has 2 to 3 decoders and AND/OR cells. Weights block performs multiply accumulate operations. Filter block depends upon on the new filter coefficients obtaining from weights block. The proposed filter is designed in MATLAB (2013a) for its performance characteristics and its constraints are verified using XILINX (verl4.7) implemented on FPGA.

Noise removal continuous to be a challenging domain of work despite of several techniques which are proposed to overcome this issue are found to be efficient and reliable. In mobile communications, the time varying nature of signals and noise makes this issue more challenging. Among conventional signal processing techniques, finite impulse response (FIR) and infinite impulse response (IIR) structures provide their own set of advantages and disadvantages. Though gamma filters in FIR and IIR forms have been suggested for noise cancellation in speech, it is bottlenecked due to issue such as longer convergence time, delay generation and inability to provide phase variation compensation. This paper presents certain techniques to overcome this issue. Firstly, a modified gamma filter with a feedback structure is used to improve MSE convergence and provide better phase variation correction. The second method uses a transfer function approach for phase correction of the filtered signal. Experiments show that the MSE and phase difference(in degree) between the filtered signal and the desired signal are lower for the proposed structure than the MSE and phase difference values obtained for the FIR filter and original gamma filter structure. Thus the suggested techniques have been found to be more reliable and efficient.

The chapter opens with the discussion of infinite impulse response filters. The complex topic of IIR filter is more intricate than FIR filter and it probes deeper linking fundamental concepts of DSP. It leads to discussion of bilinear transform which specifies the filter response sand design of an analog filter using analog filter techniques. It also shows the mapping techniques in different domains and the responses from each domain and discusses the characteristics and method of frequency preparing techniques which prepares an analog filter and ends with the notes on how analog filter which itself is a complex subject converts into a digital IIR filter. It delves deeper into the subject matter to use the software programs which can help in designing and convert them into a digital IIR design.

The design of two-channel quadrature mirror filter banks can be constructed based on real infinite impulse response (IIR) all-pass digital filters without yielding magnitude distortion. The design problem is first formulated as a phase optimization using IIR all-pass filters in the least-squares sense. Then the nonlinear phase optimization is further converted into solving an eigenproblem of an appropriate real, symmetric, and positive-definite matrix. In this paper, the minor component analysis algorithm based on the neural learning rule is exploited to the design of eigenfilter. When the learning algorithm achieves convergence, the weights of the neural system approximate the smallest eigenvector, which are the optimal filter coefficients of the IIR all-pass filters. The simulation results confirm that the proposed neural-based method can achieve accurate performance by incorporating the simple neural model.

Second-order IIR low-pass filter is widely used in digital signal processing. A fast filter algorithm without multiplication is proposed for it in this paper. A configuration method for the filter coefficient of fast algorithm is put forward, considering the characteristic of second-order IIR low-pass filter coefficient and the filter’s mathematical model. A performance analysis of fast second-order IIR low-pass filter without multiplication is shown in the paper, and the performance of the fast filter is shown by example using MATLAB simulation. What’s more, the algorithm’s rapidity is verified by an implementation of the filter on FPGA, which turns out that fast filtering algorithm takes only 54.7% of common algorithm’s operation time to realize the same filer function.

The paper presents the equalization problem of non-linear phase response of digital IIR type filters. An improved analytical method of designing a low-order equalizer is presented. The proposed approach is compared with the original method. The genetic algorithm is presented as an iterative method of optimization. The vector and matrix representation of the all-pass equalizer are shown and introduced to the algorithm. The results are compared with the analytical method. In this paper we have also proposed the use of an aging factor and setting the initial population of the genetic algorithm around the solution provided by the analytical methodology

In this article, a novel approach for infinite-impulse response IIR digital filters using particle swarm optimization PSO is presented. IIR filter is essentially a digital filter with recursive responses. Because the error surface of digital IIR filters is generally nonlinear and multimodal, so global optimization techniques are required in order to avoid local minima. This study is based on a heuristic way to design IIR filters. PSO is a powerful global optimization algorithm introduced in combinatorial optimization problems. This study finds the optimum coefficients of the IIR digital filter through PSO. It is found that the calculated values are more optimal than the FDA tool and GA available for the design of the filter in MATLAB. Design of low-pass and high-pass IIR digital filters is proposed in order to provide an estimate of the transition band. The simulation results of the employed examples show an improvement on the transition band. The stability of designed filters is described by the position of Pole-Zeros.

The paper develops a technique for the robust and stable design of digital infinite impulse response (IIR) filters. As the error surface of IIR filters is generally multi-modal, global optimization techniques are required to design efficient digital IIR filter in order to avoid local minima. In this paper a real-coded genetic algorithm (RCGA) with arithmetic- average-bound-blend crossover and wavelet mutation is applied to design the digital IIR filter. A multicriterion optimization is employed as the design criterion to obtain the optimal stable IIR filter that satisfies the different performance requirements like minimizing the Lp-norm approximation error and minimizing the ripple magnitude. The proposed real-coded genetic algorithm is effectively applied to solve the multicriterion, multiparameter optimization problems of low-pass, high-pass, band-pass, and band-stop digital filters design. The computational experiments show that the proposed method is superior or atleast comparable to other algorithms and can be efficiently used for higher order filter design.

A procedure for the design of digital filters with either a finite or infinite impulse response (FIR or IIR) is presented. Complex flatness constraints, incorporating the desired passband group delay, are used to specify the properties of non-linear-phase filters. Solutions are found using a linear combination of basis functions with zero or non-zero poles, for FIR or IIR filters, respectively. The procedure is used to design multidimensional filters for Lucas-Kanade optical flow.

In this paper for implementation of IIR digital filters, it is offered to use structures, which have a number of degrees of freedom significantly more than a number of degrees of freedom of transfer function. Such redundancy allows reducing a length of a fractional part of the filter coefficients without loss of accuracy of transfer function implementation.

A competent architecture for IIR filter is designed. It is configured and folded, which will be used in the real time applications like loud speaker and equalization of digital signal processing. A basic feature of digital signal processing is filtering. Filtering is a choosy system which passes an assured choice of frequency and attenuating the others frequency. Digital filtering is a prevailing sector of DSP allied works. A system of digital filter performs mathematical operations on a sampled or discrete time variant signal to contract or improve certain aspects of that signal. The configurable folded IIR filter for sixth order is designed using three series of second order IIR filter. This IIR filter architecture is used to carry out three second order or a one sixth order. It can be also used to execute one fourth order and one second order in parallel according to the requirement where, each second order IIR filter is designed using multiply accumulate circuit which as floating point. Here pipelining of IIR filter for second order is proposed to increase the throughput by reducing the critical path delay. The proposed sixth order IIR filter using three second order IIR filter with pipelining achieves 39.7% of increased throughput and it operates at high frequency of 85.068MHz compared with conventional MAC based architecture.

As a basic function unit of digital signal processing, digital filter design is the main subject of research in the field of digital signal processing, it is widely used in the field of communication, radar and so on. The traditional design method is difficult to satisfied high performance requirements of digital filter. A kind of simplified artificial fish swarm algorithm is introduced into optimize the design of digital filter. The effectiveness and practicability of the presented method are verified with simulation experiments. The designed IIR digital filter has little pass-band fluctuation, smaller stop-band and more attenuation. It means that that the proposed IIR digital filter design method based on simplified artificial fish swarm algorithm is effective.

This paper is on the use and performance of M-path polyphase Infinite Impulse Response (IIR) filters for channelisation, conventionally where Finite Impulse Response (FIR) filters are preferred. This paper specifically focuses on the Discrete Fourier Transform (DFT) modulated filter banks, which are known to be an efficient choice for channelisation in communication systems. In this paper, the low-pass prototype filter for the DFT filter bank has been implemented using an M-path polyphase IIR filter and we show that the spikes present at the stopband can be avoided by making use of the guardbands between narrowband channels. It will be shown that the channelisation performance will not be affected when polyphase IIR filters are employed instead of their counterparts derived from FIR prototype filters. Detailed complexity and performance analysis of the proposed use will be given in this article.

It is shown that if a rational function F (s) does not change when 1/ s is substituted instead of s then F (s) is the rational function of s + (1/ s). If the transfer function is a ratio of recursive (symmetric) polynomials, the application of this property can simplify the network synthesis, and, in case of filter synthesis, may result in new filter configurations. In addition, the method chosen for the proof can be used to create new filter transfer functions with useful characteristics. Examples are provided.

In almost all the digital filtering applications the digital infinite impulse response (IIR) filters are preferred over finite impulse response (FIR) filters because they provide much better performance, less computational cost and have smaller memory requirements for similar magnitude specifications. However, the digital IIR filters are generally multimodal with respect to the filter coefficients and therefore, reliable methods that can provide global optimal solutions are required. The artificial bee colony (ABC) algorithm is one such recently introduced meta-heuristic optimization algorithm which has proven to be more effective than other population based algorithms. But in some cases it shows insufficiency while searching the solution space resulting in a weak exchange of information and hence is not able to return better solutions. To overcome this deficiency, the opposition based learning strategy is incorporated in ABC and hence a modified version called oppositional artificial bee colony (OABC) algorithm is proposed in this paper. Duplication of members is avoided during the run which also augments the exploration ability. The developed algorithm is then applied for the design of optimal and stable digital IIR filter structure where designing of band-pass filter is carried out. To check the effectiveness of OABC, the results are compared with some well established filter design techniques and it is observed that in most cases OABC returns better or atleast comparable results.

Many acoustic signal enhancement applications require adaptive filters with a long impulse response, but with a small number of filter parameters. Fixed-poles infinite impulse response (IIR) adaptive filters based on orthonormal basis functions (OBFs) present advantages over finite impulse response filters and other IIR filters, assuring stability and fast global convergence in the adaptation of the filter parameters. A scalable algorithm is introduced for the estimation of the poles of an adaptive OBF filter from multichannel input-output data. The set of poles, common to all the acoustic channels considered, is estimated in parallel to the adaptation of the linear filter parameters. It will be shown that the result of the identification with common poles is quite robust to variations in the room transfer function, suggesting the possibility that poles may be kept fixed after estimation.

Stochastic computing (SC) has received much recent attention due to its inherent fault-tolerance and low implementation cost compared to binary radix representations. SC has been proposed for various signal processing applications such as digital filters. The prior art in stochastic FIR filters can accurately implement the desired filtering function for low-order filters, however, their accuracy degrades as the filter order increases. Moreover, stochastic IIR filters demonstrate high hardware complexity and degraded accuracy. In this paper, we propose an architecture for high-order FIR filters with negligible accuracy loss compared to fixed-point implementation. The proposed architecture requires fewer random number generators. We also describe a novel cascaded second-order direct-form II structure for IIR filters. The implementation results of the proposed design show an improvement in latency and hardware complexity compared to the stochastic architectures reported to date.

This paper describes actual problem — the increasing of detection range of the passive single bit inductively coupled RFID transponders commonly called markers. The markers are being widely used to mark the position of underground networks such as cables, pipes etc. For digital processing and noise reduction of signals from the markers two methods will be described. The first method — triple summation — goes out from the well-known double integration principle used in analog-to-digital converters modified by the division of integration (i. e. summation in the case of digital signal processing) time to the three intervals instead of two. The second method is classical application of signal filtering by bandpass IIR filter. Both method will be applied on the real signal responses from the marker recorded by digital oscilloscope.

The problem of optimal high-frequency noise suppression and low-frequency signal transmission in sampled sensor systems is considered in this paper. Low-delay digital filters with linear phase and unity magnitude at the dc limit (i.e., maximally flat) are of particular interest. Savitzky-Golay smoothers with an infinite impulse response (IIR) are introduced and their properties are explored. The filter coefficients are derived via regression analysis using orthogonal Laguerre polynomials in the time domain. A generalized form with a shape parameter included in the error-weighting function is proposed. This extension may be used to further reduce the white noise gain of the filter. A design process that determines the optimal position of the repeated real poles, either to minimize the white noise gain, or to maximize the high-frequency attenuation, for a specified low-frequency group delay, is discussed. An alternative process for the design of a generic class of maximally flat repeated-pole filters is also presented. This allows colored noise to be handled and/or additional frequency-domain constraints, such as Nyquist flatness, to be applied. Refereed/Peer-reviewed

Digital Signal Processing (DSP) , there two types of filters are used to perform the filtering operations and they are the Infinite Impulse Response (IIR) filter and the Finite Impulse Response (FIR) filter. The present output sample of an IIR filter depends on the present input samples, past input samples and past output samples, i.e IIR filter is of recursive type. Now to design the Digital IIR filter, the coefficients are essentially required. There are a numbers of techniques available for designing the IIR filter. In this paper, the design and determination of the IIR filter coefficients are introduced using computer based approach. The program based on the algorithm proposed in this paper is simulated in Matlab which provides with the satisfactory results.

Advanced electronic circuits suffer errors caused by multiple sources. For example, radiation can induce transient errors, and manufacturing variations can cause some devices to sporadically suffer errors. Fault tolerance is therefore an important issue in advanced electronic circuits. Digital filters are commonly used in many applications, and therefore, their protection against errors has been widely studied. However, infinite-impulse-response (IIR) filters have received little attention as most of the existing works focus on finite-impulse-response filters. In this brief, a technique to implement concurrent error detection in IIR filters with programmable coefficients is proposed and evaluated. The protection effectiveness is assessed through fault injection experiments that show that it can efficiently detect errors. The cost is estimated using the synthesis results for a 45-nm library. The results show that the area overhead is much lower than that of a duplicated system that can also detect errors.

Analog filter circuits that are realized in continuous-time discrete-space domain are proposed for implementing 2-D infinite impulse response (IIR) spatiotemporal transfer functions having beam-shaped passbands. These filters may be used for analog beamforming applications including seismic, audio, sonar, and ultrasonic signal processing. Unlike digital implementations, the proposed 2-D analog beam filters avoid the need for A/D conversions and digital circuitry. Importantly, the beam distortion (beam squint) due to bilinear transformation that is unavoidable in digital 2-D IIR beam filters is significantly reduced. A demonstrative example using operational amplifiers for first-order analog filters is provided.

The purpose of this paper is to study the possibility of performing practically stable and efficient frequency-space (f−x) wavefield extrapolation for the application of seismic imaging and datuming via infinite impulse response (IIR) filters. The model reduction control theory was adopted to design such IIR f−x extrapolation filters. The model reduction theory reduces the order of a given order system which, in this case, involves reducing a finite impulse response (FIR) f−x extrapolation filter system into an IIR f−x extrapolation filter system. This theory relies on decomposing the states of the given filter system into strong and weakly coupled sub-systems, and then eliminating the weakly coupled states via singular value decomposition of the Hankel and the impulse response Gramian matrices. Simulation results indicate that IIR f−x filters can be obtained, which are stable from an IIR filter design point of view. Simulations also indicate that stable seismic impulse responses and synthetics can be obtained with a reduced system model order and, hence, less computational efforts with respect to the number of complex multiplications and additions per output sample. It is hoped that this study will open new possibilities for researchers to reconsider designing IIR f−x explicit depth extrapolation filters due to their expected computational savings and wavenumber response accuracy, when compared to the FIR f−x explicit depth extrapolation filters.

Hybrid optimization algorithm is applied for designing stable infinite impulse response (IIR) digital filter based on L1-approximation error criterion. The proposed Hybrid method calculates the optimal filter coefficients by exploring and exploiting the search space locally as well globally. The filter designed based on L1-approximation error possesses flat passbands and stopbands in comparison to that of least square design and the minimax approach. A comparison with other design techniques is made, demonstrating that the proposed hybrid approach can obtain better digital IIR filters than the existing Genetic Algorithm (GA) based methods. KeywordsIIR filters, Hybrid search algorithm, L 1-approximation error, Stability.

A Canonic-Signed-Digit-(CSD-) coded genetic algorithm (GA) is proposed to find the optimal design of robustly stable infinite impulse response digital filter (IIR). Under the characteristics of the CSD structure, the circuit of the filter can be simplified and also the calculation speed can be raised to increase the hardware’s efficiency. However, the design of CSD has a big challenge: the CSD structure of the system parameters will be destroyed by an optimal design procedure. To solve this problem, in this research a CSD-coded GA is proposed so that the CSD structure can be maintained. Moreover, the robustly stable IIR filters design problem is included in this paper. The robustness of the IIR filters is achieved by ensuring that all poles of the filters are located inside a diskD(α,r)contained in the unit circle, in whichαis the center,ris the radius of the disk, and|α|+r<1. Consequently, in this paper, a new and more efficientD(α,r)-stability criterion will be derived and then embedded in GA for the design of robust IIR filters. It is worthwhile to note that to design an IIR filter simultaneously with CSD-structured parameters and robust stability is difficult and is not well explored so far. An example will be presented to show the efficiency of the proposed strategy for design of IIR filters.

This paper presents the design of Optimal Infinite-Impulse Response (IIR) digital filters using Genetic Algorithm (GA). IIR filter is essentially a digital filter with Recursive responses. Since the error surface of digital IIR filters is generally nonlinear and multimodal, global optimization techniques are required in order to avoid local minima. This paper presents heuristic way for the designing IIR filters. GA is a powerful global optimization algorithm introduced in combinatorial optimization problems. The paper finds the optimum Coefficients of IIR digital filter through GA. Design of Lowpass and High pass IIR digital filter is proposed to provide estimate of transition band. It is found that the calculated values are more optimal than fda tool available for the design of filter in MATLAB. The simulation result of the employed examples shows an improvement on transition band and mean-square-error (MSE). The position of pole-zero is also presented to describe stability and results are compared with Simulated Annealing (SA) method.

The possibility of changing the transfer function of a frequency compensation filter, without modifying its topology, allows to synthesize a feedback regulator of power converters that can be used in a wide variety of applications. By programming the transfer function, the dynamics of the filter can be optimized for each power cell obtaining the desired closed loop behavior. In principle, the filter can be integrated within the power cell and programmed according to specific needs.Digital filters own this characteristic. Common analog filters, instead, does not offer such a possibility, since their transfer function depend upon their topology. A recursive linear filter in the discrete time, with programmable gains, allows its implementation, offering the same advantages of digital controllers, while avoiding some of their limitations. This paper considers a possible solution based upon switched capacitor circuits, made programmable by multiplying digital to analog converters. In some cases, this s...

In this work, the design of sampled-data infinite impulse response (IIR) filters based on time-mode signal processing (TMSP) circuits is presented. Time-mode signal processing, defined as the processing of sampled analog information using time-difference variables, is still a relatively new technology, and therefore, there is still much development needed to extend the technology into a general signal-processing tool. In this work, a set of general building blocks will be introduced that perform the most basic mathematical operations in the time-mode. By arranging these basic structures, higher-order time-mode systems, specifically, time-mode IIR filters, will be realized. A second low-pass time-mode IIR filter is implemented using discrete components. Measured results confirmed that the circuit performed low-pass filtering, providing a maximum SNR of 45.2 dB and SNDR of 35.3 dB.

This paper explores the pole-placement design problem of a robust stable infinite-impulse-response (IIR) filter to attenuate or eliminate the undesired measurement noise and proposes a strategy based on an adaptive differential evolution (ADE) algorithm to design a filter. The results are compared to the results of other popular evolutionary algorithms, e.g., particle swarm optimization (PSO), genetic algorithm (GA), and improved genetic algorithm (IGA). The stability robustness for an IIR filter will be achieved by placing all poles inside a disk D(α, r) contained in the unit disk, in which α is the center, and r is the radius of the disk. This investigation first uses a robust stability criterion, called the D(α, r)-stability criterion, to ensure that digital filter poles lie inside a disk D(α, r). The proposed strategy checks the criterion during differential evolution (DE) and adaptively adjusts the DE parameters, depending on the current DE performance. This paper also introduces two design examples of a bandpass IIR filter and a low-pass IIR filter for the measurement of a speech signal. These examples show that the proposed strategy performance based on the proposed ADE is better than designs based on PSO, GA, and IGA. Finally, this paper implements an IIR filter on the field-programmable gate array (FPGA) chip to verify the designed filter performance in practical electronic devices and uses speech signals as an input signal to the FPGA chip to verify that the measurement noise of the speech signal is attenuated by the designed IIR filter.

The research of applying evolutionary algorithms (EAs) to digital infinite-impulse response (IIR) filter design has gained much attention in recent years. Previously, most works treated digital IIR filter design as a single objective optimization problem of minimizing the magnitude response error with supplementary conditions. While the lack of considering the linear phase response error and the order may result in the loss of control on the structural flexibility, the distortion of output, and the dependency on pre-knowledge. The aim of this paper is to develop proper IIR filter designing method that (1) can provide relatively more complete optimal solutions with equal consideration of magnitude response, linear phase response and the order of structure; (2) can simultaneously optimize the structure and coefficients of digital IIR filter to obtain relatively better linear phase response and lower order, besides the good magnitude response. To achieve these targets, the digital IIR filter design problem is treated as a multi-objective optimization problem in this paper. A new local search operator enhanced multi-objective evolutionary algorithm (LS-MOEA) is specifically proposed for such kind of multi-objective optimization problems. To evaluate the effectiveness and efficiency of LS-MOEA, we experimentally compare it with classical methods and previously effective EAs for digital IIR filter design on four typical IIR filter design cases. Experimental results show that the proposed method can effectively improve the linear phase response of the designed filter, and can obtain filter of lower order. Besides, it achieves these by relatively much lower computational cost than compared EAs.

Infinite impulse response filters have not been used extensively in active noise and vibration control applications. The problems are mainly due to the multimodal error surface and instability of adaptive IIR filters used in such applications. Considering these, in this paper a new adaptive recursive RLS-based fast-array IIR filter for active noise and vibration control applications is proposed. At first an RLS-based adaptive IIR filter with computational complexity of order O(n^2) is derived, and a sufficient condition for its stability is proposed by applying passivity theorem on the equivalent feedback representation of this adaptive algorithm. In the second step, to reduce the computational complexity of the algorithm to the order of O(n) as well as to improve its numerical stability, a fast array implementation of this adaptive IIR filter is derived. This is accomplished by extending the existing results of fast-array implementation of adaptive FIR filters to adaptive IIR filters. Comparison of the performance of the fast-array algorithm with that of Erikson's FuLMS and SHARF algorithms confirms that the proposed algorithm has faster convergence rate and ability to reach a lower minimum mean square error which is of great importance in active noise and vibration control applications.