Design Of IIR Digital Filters Research Articles

Inclined planes system optimization: Theory, literature review, and state-of-the-art versions for IIR system identification

The Inclined Planes System Optimization (IPO) algorithm is recent algorithm that uses Newton’s second law to perform optimization. After conducting a thorough literature review, this paper proposes an improved version of IPO called IIPO. This improvement is achieved by changing exploratory and exploitative behavior of the standard IPO proportional to the progress of optimization (iteration). The IIPO is employed for optimizing IIR digital filter design, which is a challenging engineering problem. Adaptive IIR modeling as a multimodal optimization problem is designed and developed under system identification structure with an appropriate single-objective function in the frequency domain. Implementations are performed in both modeling cases with same and reduced orders, and under two identification forms with and without environmental additive noise. The results are reported along with various analyzes compared to a wide range of IPO variants. The statistical results on 100 independent trials show a success of more than 90% of cases, the proposed IIPO algorithm substantially outperforms other comparative algorithms in terms of accuracy of estimated coefficients, convergence, fitness, output responses, noise analysis, stability, and reliability.11All source codes are fully and publicly available at https://github.com/ali-ece.

An Enhanced Slime Mould Algorithm and Its Application for Digital IIR Filter Design

In the past few decades, metaheuristic algorithms (MA) have been developed tremendously and have been successfully applied in many fields. In recent years, a large number of new MA have been proposed. Slime mould algorithm (SMA) is a novel swarm-based intelligence optimization algorithm. SMA solves the optimization problem by imitating the foraging and movement behavior of slime mould. It can effectively obtain a promising global optimal solution. However, it still suffers some shortcomings such as the unstable convergence speed, the imprecise search accuracy, and incapability of identifying a local optimal solution when faced with complicated optimization problems. With the purpose of overcoming the shortcomings of SMA, this paper proposed a multistrategy enhanced version of SMA called ESMA. The three enhanced strategies are chaotic initialization strategy (CIS), orthogonal learning strategy (OLS), and boundary reset strategy (BRS). The CIS is used to generate an initial population with diversity in the early stage of ESMA, which can increase the convergence speed of the algorithm and the quality of the final solution. Then, the OLS is used to discover the useful information of the best solutions and offer a potential search direction, which enhances the local search ability and raises the convergence rate. Finally, the BRS is used to correct individual positions, which ensures the population diversity and enhances the overall search capabilities of ESMA. The performance of ESMA was validated on the 30 IEEE CEC2014 functions and three IIR model identification problems, compared with other nine well-regarded and state-of-the-art algorithms. Simulation results and analysis prove that the ESMA has a superior performance. The three strategies involved in ESMA have significantly improved the performance of the basic SMA.

Development of a Low-Cost and Effisient ECG devices with IIR Digital Filter Design


 
 
 
 Measurement of biosignals such as electrocardiograph has the interpretation of noise from other signals. The noise can interfere with the measurement of the heart signal and make the measurement inaccurate, so the purpose of this study is to make a 6-Lead Electrocardiogram module with an Arduino-Based Digital Filter. By using a digital filter. The contribution of this research is the use of digital filters to eliminate noise in electrocardiograph signals. This research uses Infinite Impulse Filter digital filters such as Butterworth, Chebyshev I, Chebyshev II, and Elliptic in order 2, 4, 6, 8, and 10. The study was conducted by providing input from the Function Generator on Arduino which has been applied digital filters with Frequency with 0.5Hz – 100Hz cut-off. The instrument is compared with a factory electrocardiograph. Filter measurements using 460 input data. Butterworth filter with the greatest emphasis on order 8 frequency 0.5Hz produces an emphasis of -5.74298158 dB and a frequency of 100Hz produces an emphasis of -5.93529424 dB. The Chebyshev I filter has the greatest emphasis on order 6 frequency 0.5Hz producing an emphasis of -3.27104076 dB and on order 8 frequency 100Hz producing an emphasis of -5.08730424 dB. Chebyshev II filter the biggest emphasis on the order of frequency 0.5Hz produces a suppression of -44,66011104 dB and 80Hz frequency produces a suppression of -37,3653957 dB. Elliptic filters the greatest emphasis on order 6 frequency 0.5Hz produces an emphasis on -1.55429354 dB and 100Hz frequency on order 8 produces an emphasis on -2.2849115 dB. The results showed that what was appropriate with the cut-off frequency was the Butterworth order 8 filter which was suitable for the application of the Electrocardiograph signal filter because it had bandwidth that suppressed the signal outside the cut-off frequency. The results of this study can be implemented on a 6-Lead ECG module to eliminate noise or interference when tapping ECG signals.
 
 
 

Implementation of digital IIR filter design based on field programmable gate array

Abstract Programmable Gate Array (FPGA) software is widely used in digital signal processing (DSP), and DSP algorithms are used in many fields, such as voice signal processing, audio signal processing, picture processing, information systems, system control, etc. Using digital filters as an example, this article uses these three methods to apply filter algorithms and detail the design steps and final validation of the simulation. Based on the recently published low-level parallel filter FIR structure, this document proposes a new design to reduce device complexity. A large number of devices can be stored with the new system. For example, for FIR 576 click filters, when the level of parallelism changes from 12 to 72, the new system can double from 1755 to 3375 at the cost of 21 to 4658 additions and delay elements 1516 to 4749, respectively. This algorithm not only reduces the complexity of computing, but also partially maintains the multiplier aggregation structure, which leads to efficient implementation. This article presents hybrid programming methods that use VB and Matlab to design digital filters.

Low latency IIR digital filter design by using metaheuristic optimization algorithms

Low latency IIR digital filter design by using metaheuristic optimization algorithms

Design and Analysis of Digital IIR, Fir Bandpass Filter using DSK6713 Kit

A digital filter is advantageous over analog filter. Some of its advantages are less complexity, flexibility, portability when compared with analog filters. In this paper, the design of digital IIR and FIR band pass filter is done using DSK6713 hardware kit, the software used is code composer studio 6.0.1. This code composer studio 6.0.1 is used to write the code in c language, which is then dumped on to DSK6713 kit, fda tool of matlab is used for designing coefficients for IIR and FIR filter. Further, the detailed design steps are illustrated in this paper

A structure evolution-based design for stable IIR digital filters using AMECoDEs algorithm

This paper proposes a subsystem-based structure evolution algorithm for stable IIR digital filter design. The method designs the IIR digital filter through optimizing the filter structure. A filter structure is defined as the connection of the subsystems. A subsystem is a 2-order IIR digital structure with uncertain parameters. Subsystems are randomly connected with the constraints of no feedback branches between subsystems. The subsystem’s parameters and the connections between subsystems are optimized by evolutionary algorithms. An adaptive multiple-elites-guided composite differential evolution algorithm (AMECoDEs) is used to optimize this problem. Four classic types of filters, lowpass, highpass, bandpass and bandstop filters are designed. Five state-of-the-art evolutionary algorithms are compared. The simulation results show that AMECoDEs holds the first place on comprehensive performance and convergence rate. At the same time, the poles of filters all reside within the unit circle, which validates the stability of the IIR digital filters.

A Sequential Partial Optimization Algorithm with Guaranteed Convergence for Minimax Design of IIR Digital Filters

Challenges for optimal design of infinite impulse response digital filters include the high nonconvexity of design problem and inevitable stability constraints on the filters. To reduce the nonconvexity and tackle the stability constraints, a sequential partial optimization (SPO) algorithm was recently developed to divide the design problem into a sequence of subproblems, each updating only two second-order denominator factors. But the convergence of that algorithm is not guaranteed. By applying an incremental update with an optimized step length in each subproblem, this paper presents an improved SPO algorithm which is guaranteed to converge to a Karush–Kuhn–Tucker (not necessarily global) solution of the design problem. This paper also extends the SPO algorithm to a more general case where the number of denominator factors optimized in the subproblems can be any positive number smaller than half of the denominator order. Convergence performance of the algorithm is shown by the design of two example filters with typical specifications widely adopted in the literature. Comparisons with state-of-the-art methods demonstrate that the improved SPO algorithm obtains better filters than the competing methods in terms of the maximum magnitude of frequency-response error.

The Design Of Intelligent Filter For EEG

EEG data processing method is usually digital filter designed by the traditional method. Its disadvantage is the transition zone is wide and the filtering effect is poor. Using an improved particle swarm optimization algorithm on IIR digital filters design, the performances of filters designed by various methods are compared and analyzed. Experiments illustrate particle swarm optimization algorithm is effective in IIR filter design and its performance is promising.

Design of Digital IIR Filter with Conflicting Objectives Using Hybrid Predator–Prey Optimization

The design of digital IIR filter as a single-objective optimization problem using evolutionary algorithms has gained much attention in the previous years. In this paper, the design of filter is treated as a multi-objective problem by simultaneously minimizing the magnitude response error, linear phase response error and optimal order within the stability constraints. The global search technique, predator–prey optimization (PPO), has been applied to design the digital IIR filter. The global search technique has been hybridized with binary successive approximation (BSA)-based evolutionary search method for exploring the search space locally. The relative performance of PPO and hybrid PPO has been evaluated by applying these techniques to standard mathematical test functions. The above-proposed hybrid search technique has been applied to achieve the solution for multi-parameter and multi-objective optimization problem of low-pass (LP), high-pass (HP), band-pass (BP) and band-stop (BS) digital IIR filter design. The results obtained from the proposed technique are compared with the results of other algorithms applied by other researchers for the design of digital IIR filter.

IIR digital filter design for powerline noise cancellation of ECG signal using arduino platform

Powerline noise has been one of significant noises of Electrocardiogram (ECG) signal measurement. This noise is characterized by a sinusoidal signal which has 50 Hz of noise and 0.3 mV of maximum amplitude. This paper describes the design of IIR Notch filter design to reject a 50 Hz power line noise. IIR filter coefficients were calculated using pole placement method with three variations of band stop cut off frequencies of (49-51)Hz, (48 - 52)Hz, and (47 - 53)Hz. The algorithm and coefficients of filter were embedded to Arduino DUE (ARM 32 bit microcontroller). IIR notch filter designed has been able to reject power line noise with average square of error value of 0.225 on (49-51) Hz filter design and 0.2831 on (48 - 52)Hz filter design.

Structure Evolution Based Optimization Algorithm for Low Pass IIR Digital Filter Design

Digital filters are generally designed by identifying the transfer functions. Most researches are focused on the goal of approaching the desired frequency response, and take less additional consideration of structure characteristics which can greatly affect the performance of the digital filter. This paper proposes a structure-evolution based optimization algorithm (SEOA) which allows the integrated consideration of structure issues and frequency response specifications in design stage. The method generates digital filter structures by a structurally automatic-generation algorithm (SAGA) which can randomly generate and effectively represent digital structures. The structures, seen as chromosomes, are evolved over genetic algorithm (GA) for the search of the optimal solution in structure space. They are evaluated according to the mean squared error (MSE) between the designed and the desired frequency responses. Simulation results validate that the algorithm designs diversified structures of digital filters and they meet target frequency specifications and structure constraints tightly. It is a promising way for optimized and automated design of digital filters.

Design of two-dimensional IIR digital filters by using a novel hybrid optimization algorithm

This paper proposes a hybrid optimization algorithm named as BBO–PSO, which is a combination of biogeography-based optimization (BBO) and particle swarm optimization (PSO). In BBO–PSO, the whole population will be split into several subgroups and BBO is employed for local search in each subgroup independently to achieve the different local optima while PSO is employed for global search based on the local optima to achieve the global optimum. The test results on the benchmark functions show that BBO–PSO has powerful search ability with great robustness. Furthermore, the proposed algorithm is applied to the design of the 2-D IIR digital filters and the simulation results show that it outperforms the existing methods on this problem.

Hybrid heuristic search method for design of digital IIR filter with conflicting objectives

The design of digital IIR filter design by using evolutionary algorithms has gained much attention in the previous years. Most of the researchers treated the design problem as a single objective optimization problem and applied the techniques for minimizing the magnitude response error. In this paper the design of filter is treated as a multi-objective problem by simultaneously minimizing the magnitude response error, linear phase response error and optimal order along with meeting the stability criterion. A hybrid heuristic search technique having differential evolution (DE) method as a global search technique and binary successive approximation based evolutionary search method as a local search technique has been proposed. Based on mean value of population, new mutation strategies have been proposed. The above proposed hybrid heuristic search technique has been applied effectively to solve the multi-parameter and multi-objective optimization problem of low-pass, high-pass, band-pass and band-stop digital IIR filter design. The obtained results reveal that the proposed technique with new proposed mutation strategies performs better than the already existing mutation strategies of DE and other algorithms applied by other researchers for the design of digital IIR filter.

Design of IIR digital filters with critical monotonic passband amplitude characteristic: A case study

A case study is reported related to the design of IIR digital filters exhibiting critical monotonic amplitude characteristic (CMAC) in the pass band. This kind of amplitude characteristic offers several advantages as compared to its non-monotonic counterparts, although it has not been studied thoroughly so far, if at all. After giving a short overview of the way of CMACs generation, arguments will be listed in favor of the IIR version of the digital filter function realization. Next, the IIR implementation of the digital filters will be considered in short. The main part of the paper will be devoted to the design sequence of this kind of filters which will be illustrated on the example of a band-pass filter obtained by a set of transformations from an all-pole low-pass analogue prototype. This will be the first time a CMAC band-pass IIR digital filter is reported.

A decentralized quantum-inspired particle swarm optimization algorithm with cellular structured population

This paper proposes a decentralized form of quantum-inspired particle swarm optimization (QPSO) with cellular structured population (called cQPSO) for keeping the population diversity and balancing the global and local search. The cQPSO is further improved by re-designing the local attractor in the sub-population (called cQPSO-lbest) in order to accelerate the diffusion of the best solution and thus enhance the performance of cQPSO. The particles in cQPSO and cQPSO-lbest are distributed in a two-dimensional (2D) grid and only allowed to interact with their neighbors according to the specified neighborhood, which plays a role in exploiting the search space inside the neighborhood. The overlapping particles work for delivering the information among the nearest neighborhoods acting as exploring the search space with diffusion of solutions during the evolutionary process. Theoretical studies are made to analyze the global convergence of cPSO and cQPSO-lbest based on the theory of probabilistic metric space. We systematically investigate the performance of cQPSO-lbest on 42 benchmark functions with different properties (including unimodal, multimodal, separated, shifted, rotated, noisy, and mis-scaled) and compare with a set of PSO variants with different topologies and swarm-based evolutionary algorithms (EAs). The experimental results demonstrate the better performance of cQPSO-lbest. Moreover, two real-world problems, which are two-dimensional (2D) IIR digital filter design and economic dispatch (ED) problem from power systems area, are used to evaluate cQPSO-lbest and the experimental results verified the advantages of cQPSO-lbest.

Design of Digital IIR Filter with Conflicting Objectives Using Hybrid Gravitational Search Algorithm

In the recent years, the digital IIR filter design as a single objective optimization problem using evolutionary algorithms has gained much attention. In this paper, the digital IIR filter design is treated as a multiobjective problem by minimizing the magnitude response error, linear phase response error and optimal order simultaneously along with meeting the stability criterion. Hybrid gravitational search algorithm (HGSA) has been applied to design the digital IIR filter. GSA technique is hybridized with binary successive approximation (BSA) based evolutionary search method for exploring the search space locally. The relative performance of GSA and hybrid GSA has been evaluated by applying these techniques to standard mathematical test functions. The above proposed hybrid search techniques have been applied effectively to solve the multiparameter and multiobjective optimization problem of low-pass (LP), high-pass (HP), band-pass (BP), and band-stop (BS) digital IIR filter design. The obtained results reveal that the proposed technique performs better than other algorithms applied by other researchers for the design of digital IIR filter with conflicting objectives.

Fast Design of IIR Digital Filters With a General Chebyshev Characteristic

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.

Real Coded Genetic Algorithm for Design of IIR Digital Filter with Conflicting Objectives

A solution methodology for the design of digital infinite impulse response (II R) filter considering multiple conflicting objectives has been proposed. The nucleus of the method is that multiple objectives can be attuned suitably, to optimize the performance in pass bands, stop bands and transition bands of IIR digital filters. The p roposed method uses multiobjective optimization approach for designing stable IIR filter using real-coded genetic algorithm (RCGA). Digital IIR filters are designed by minimizing magnitude response and phase response simultaneously, using weighted sum approach. The value of weights are searched using RCGA along with filter coefficients thus assigning different weight vector to each indiv idual population thereby finding multiple pareto-optimal solutions in one simulation run. The order of the filter is controlled by a contro l gene whose value is also optimized along with the filter coefficients to obtain optimum order of designed IIR filter. The compu tational experiments show that the proposed approach gives better digital IIR filters than the existing genetic algorithm based methods.

A second order s-to-z transform and its implementation to IIR filter design

Purpose – The purpose of this paper is to design a tool for IIR digital filters obtained from analog prototypes, which preserves simultaneously the amplitude and the group delay response. Design/methodology/approach – A new s-to-z transform is developed based on a second order formula used for numerical integration of differential equations. Stability of the newly obtained transfer functions in the z-domain is proved to be preserved. Distortions introduced by the new transform into the original amplitude and group delay responses are studied. Findings – The new formula, when implemented to all-pole prototypes, exhibits lower selectivity than the original while reducing the pass-band group delay distortions. In the same time its structure is importantly simpler than the functions obtained by the well-known bilinear transform. When implemented to a prototype having “all kinds” of transmission zeros the resulting filter has almost ideally the same characteristic as the prototype. Research limitations/implications – The new transform may be used exclusively to synthesize even order filters. The new function is twice the order of the analog prototype. This kind of transformations are used to design IIR digital filters only. Low-pass transfer functions were studied being prototypes for all other cases. Originality/value – This is a new result never mentioned in the literature. Its effectiveness is confined to a niche problem when simultaneous sharp selectivity and low group delay distortions are sought.