L1-Norm and LMS Based Digital FIR Filters Design Using Evolutionary Algorithms
The suggested work in this paper involves the construction of digital filters by utilizing optimization algorithms to compute optimum filter coefficients in such a way that the designed filter's magnitude response is identical to the ideal one. The proposed work takes a nature-inspired approach...
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| Published in | Journal of electrical engineering & technology Vol. 19; no. 1; pp. 753 - 762 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Singapore
Springer Nature Singapore
01.01.2024
Springer Nature B.V 대한전기학회 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1975-0102 2093-7423 |
| DOI | 10.1007/s42835-023-01589-7 |
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| Abstract | The suggested work in this paper involves the construction of digital filters by utilizing optimization algorithms to compute optimum filter coefficients in such a way that the designed filter's magnitude response is identical to the ideal one. The proposed work takes a nature-inspired approach to optimizing the design of 20th order linear phase finite impulse response (FIR) based low pass, high pass and band pass filters. This approach involves the cuckoo search optimization algorithm (CSA) and Grasshopper optimization algorithms (GOA) by minimizing the least mean square error function and L
1
-norm based ones. These GOA and CSA are used to find the best possible values for the filter coefficients. The bench mark algorithm to design the FIR filter as Parks–McClellan approach and other recently published optimization algorithms are used to prove the superiority of proposed designs. Compared with PM method, real coded genetic algorithm, Cat swarm, Particle swarm optimization and some hybrid optimization based ones, the proposed design results have been outperform. Moreover, the proposed FIR filters give the best outcome, effectively meeting the target with decreased pass band ripples and higher attenuation in the stop band with a least execution time. |
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| AbstractList | The suggested work in this paper involves the construction of digital filters by utilizing optimization algorithms to compute optimum filter coefficients in such a way that the designed filter's magnitude response is identical to the ideal one. The proposed work takes a nature-inspired approach to optimizing the design of 20th order linear phase finite impulse response (FIR) based low pass, high pass and band pass filters. This approach involves the cuckoo search optimization algorithm (CSA) and Grasshopper optimization algorithms (GOA) by minimizing the least mean square error function and L
1
-norm based ones. These GOA and CSA are used to find the best possible values for the filter coefficients. The bench mark algorithm to design the FIR filter as Parks–McClellan approach and other recently published optimization algorithms are used to prove the superiority of proposed designs. Compared with PM method, real coded genetic algorithm, Cat swarm, Particle swarm optimization and some hybrid optimization based ones, the proposed design results have been outperform. Moreover, the proposed FIR filters give the best outcome, effectively meeting the target with decreased pass band ripples and higher attenuation in the stop band with a least execution time. The suggested work in this paper involves the construction of digital flters by utilizing optimization algorithms to compute optimum flter coefcients in such a way that the designed flter's magnitude response is identical to the ideal one. The proposed work takes a nature-inspired approach to optimizing the design of 20th order linear phase fnite impulse response (FIR) based low pass, high pass and band pass flters. This approach involves the cuckoo search optimization algorithm (CSA) and Grasshopper optimization algorithms (GOA) by minimizing the least mean square error function and L1-norm based ones. These GOA and CSA are used to fnd the best possible values for the flter coefcients. The bench mark algorithm to design the FIR flter as Parks–McClellan approach and other recently published optimization algorithms are used to prove the superiority of proposed designs. Compared with PM method, real coded genetic algorithm, Cat swarm, Particle swarm optimization and some hybrid optimization based ones, the proposed design results have been outperform. Moreover, the proposed FIR flters give the best outcome, efectively meeting the target with decreased pass band ripples and higher attenuation in the stop band with a least execution time. KCI Citation Count: 2 The suggested work in this paper involves the construction of digital filters by utilizing optimization algorithms to compute optimum filter coefficients in such a way that the designed filter's magnitude response is identical to the ideal one. The proposed work takes a nature-inspired approach to optimizing the design of 20th order linear phase finite impulse response (FIR) based low pass, high pass and band pass filters. This approach involves the cuckoo search optimization algorithm (CSA) and Grasshopper optimization algorithms (GOA) by minimizing the least mean square error function and L1-norm based ones. These GOA and CSA are used to find the best possible values for the filter coefficients. The bench mark algorithm to design the FIR filter as Parks–McClellan approach and other recently published optimization algorithms are used to prove the superiority of proposed designs. Compared with PM method, real coded genetic algorithm, Cat swarm, Particle swarm optimization and some hybrid optimization based ones, the proposed design results have been outperform. Moreover, the proposed FIR filters give the best outcome, effectively meeting the target with decreased pass band ripples and higher attenuation in the stop band with a least execution time. |
| Author | Rajasekhar, K. |
| Author_xml | – sequence: 1 givenname: K. surname: Rajasekhar fullname: Rajasekhar, K. email: rajakarumuri87@gmail.com organization: Department of Electronics and Communication Engineering, University College of Engineering Kakinada, JNTUK |
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| ContentType | Journal Article |
| Copyright | The Author(s) under exclusive licence to The Korean Institute of Electrical Engineers 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. The Author(s) under exclusive licence to The Korean Institute of Electrical Engineers 2023. |
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| References | Gupta V et al (2021) Nonlinear technique-based ECG signal analysis for improved healthcare systems. In: Proceedings of international conference on communication and computational technologies: ICCCT, Springer Singapore JayaweeraALPakiyarajahDEdussooriyaCUMinimax design of MD sparse FIR filters with arbitrary frequency response using SOCPIEEE Trans Circ Syst II Expr Briefs202269524032407 GuptaVDetection of R-peaks using fractional Fourier transform and principal component analysisJ Ambient Intelld Human Comput20221396197210.1007/s12652-021-03484-3 GuptaVMittalMMittalVFrWT-PPCA-based R-peak detection for improved management of healthcare systemIETE J Res202110.1080/03772063.2021.1982412 PrashanthBUVAhmedMRKounteMRDesign and implementation of DA FIR filter for bio-inspired computing architectureInt J Electr Comput Eng20211121709 GuptaVMittalMMittalVA simplistic and novel technique for ECG signal pre-processingIETE J Res202210.1080/03772063.2022.2135622 OliveiraHAPetragliaAPetragliaMRFrequency domain FIR filter design using fuzzy adaptive simulated annealingCirc Syst Sig Process20092889991110.1007/s00034-009-9128-1 Parks TW and Sidney Burrus C (1987) Digital filter design, Wiley-Interscience BoudjelabaKRosFChikoucheDAn efficient hybrid genetic algorithm to design finite impulse response filtersExpert Syst Appl201441135917593710.1016/j.eswa.2014.03.034 GuptaVApplication of chaos theory for arrhythmia detection in pathological databasesInt J Med Eng Inform2023152191202 GuptaVAn efficient AR modelling-based electrocardiogram signal analysis for health informaticsInt J Med Eng Inform202214174894439526 KarthickRDesign and analysis of linear phase finite impulse response filter using water strider optimization algorithm in FPGACirc Syst Sig Process20224195254528210.1007/s00034-022-02034-2 GuptaVAn adaptive optimized schizophrenia electroencephalogram disease prediction frameworkWirel Pers Commun202313021191121310.1007/s11277-023-10326-2 GuptaVMittalMMittalVA novel FrWT based arrhythmia detection in ECG signal using YWARA and PCAWirel Pers Commun202212421229124610.1007/s11277-021-09403-1 GuptaVPCA as an effective tool for the detection of R-peaks in an ECG signal processingInt J Syst Assur Eng Manag202213523912403444285210.1007/s13198-022-01650-0 SahaSKGhoshalSPKarRMandalDCat swarm optimization algorithm for optimal linear phase FIR filter designISA Trans201352678179410.1016/j.isatra.2013.07.009 Yang X-S and Deb S (2010) Engineering optimisation by cuckoo search. arXiv preprint ar Xiv:1005.2908 KarabogaNCetinkayaBIDesign of digital FIR filters using differential evolution algorithmCirc Syst Signal Process2006255649660234392610.1007/s00034-005-0721-7 SaremiSMirjaliliSLewisAGrasshopper optimisation algorithm: theory and applicationAdv Eng Softw2017105304710.1016/j.advengsoft.2017.01.004 YadavSA novel approach for optimal design of digital FIR filter using grasshopper optimization algorithmISA Trans202110819620610.1016/j.isatra.2020.08.032 GuptaVPre-processing based ECG signal analysis using emerging toolsIETE J Res202310.1080/03772063.2023.2202162 Gupta V et al (2023) Adaptive Autoregressive Modeling Based ECG Signal Analysis for Health Monitoring. Optimization Methods for Engineering Problems, Apple Academic Press, pp 1–15 ReddyKSSahooSKAn approach for FIR filter coefficient optimization using differential evolution algorithmAEU-Int J Electron Commun201569110110810.1016/j.aeue.2014.07.019 Luitel B, Venayagamoorthy GK (2008) Differential evolution particle swarm optimization for digital filter design. In: IEEE congress on evolutionary computation (IEEE World Congress on Computational Intelligence), pp 3954–3961 TsutsumiSSuyamaKDesign of FIR filters with discrete coefficients using ant colony optimizationElectron Commun Jpn2014974303710.1002/ecj.11522 ArchanaSMahapatraRKPanigrahiSPDEPSO and PSO-QI in digital filter designExpert Syst Appl201138109661097310.1016/j.eswa.2011.02.140 GuptaVECG signal analysis based on the spectrogram and spider monkey optimisation techniqueJ Inst Eng (India) Ser B2023104115316410.1007/s40031-022-00831-6 MandalSDesign of optimal linear phase FIR high pass filter using craziness based particle swarm optimization techniqueJ King Saud Univ-Comput Inform Sci20122418392 Chilamkurthi DP, Tirupatipati GC, Sulochanarani J, Pamula VK (2017) Design of optimal digital FIR filters using TLBO and Jaya algorithms. In: International conference on communication and signal processing (ICCSP 2017), pp 0538–0541 MitraSKDigital signal processing: a computer-based approach2006New YorkMcGraw-Hill Higher Education SharmaIPerformance of swarm based optimization techniques for designing digital FIR filter: a comparative studyEng Sci Technol, An Int J201619315641572351821710.1016/j.jestch.2016.05.013 Gupta V, Rathi N (2010) Various objects detection using Bayesian theory. In: Proceedings of the international conference on computer applications II, Pondicherry, India, Research Publishing Services KumarAKuldeepBDesign of M-channel cosine modulated filter bank using modified Exponential windowJ Franklin Inst2012349313041315289934010.1016/j.jfranklin.2012.01.013 Yadav S, Kumar M, Yadav R, Kumar A (2020) A novel approach for optimal digital FIR filter design using hybrid Grey Wolf and Cuckoo search optimization. In: First International Conference on Computing, Communications, and Cyber-Security (IC4S 2019), Springer Singapore, pp 329–343 JiangASparse FIR filter design via partial 1-norm optimizationIEEE Trans Circ Syst II Expr Briefs201967814821486 AbabnehJIBatainehMHLinear phase FIR filter design using particle swarm optimization and genetic algorithmsDigital Signal Process200818465766810.1016/j.dsp.2007.05.011 GuptaVA design of bat-based optimized deep learning model for EEG signal analysisMultimed Tools Appl202310.1007/s11042-023-15462-2 BUV Prashanth (1589_CR31) 2021; 11 V Gupta (1589_CR10) 2022; 124 R Karthick (1589_CR30) 2022; 41 V Gupta (1589_CR7) 2022 S Tsutsumi (1589_CR18) 2014; 97 SK Saha (1589_CR19) 2013; 52 V Gupta (1589_CR14) 2023 V Gupta (1589_CR6) 2022; 14 AL Jayaweera (1589_CR28) 2022; 69 1589_CR35 V Gupta (1589_CR12) 2022; 13 1589_CR16 JI Ababneh (1589_CR36) 2008; 18 V Gupta (1589_CR9) 2022; 13 1589_CR37 I Sharma (1589_CR23) 2016; 19 A Kumar (1589_CR29) 2012; 349 HA Oliveira (1589_CR22) 2009; 28 1589_CR4 S Archana (1589_CR25) 2011; 38 N Karaboga (1589_CR20) 2006; 25 1589_CR2 V Gupta (1589_CR8) 2023 1589_CR5 V Gupta (1589_CR3) 2023; 15 SK Mitra (1589_CR1) 2006 S Mandal (1589_CR21) 2012; 24 A Jiang (1589_CR27) 2019; 67 K Boudjelaba (1589_CR17) 2014; 41 KS Reddy (1589_CR32) 2015; 69 S Saremi (1589_CR34) 2017; 105 V Gupta (1589_CR11) 2021 V Gupta (1589_CR13) 2023; 104 1589_CR24 S Yadav (1589_CR33) 2021; 108 V Gupta (1589_CR15) 2023; 130 1589_CR26 |
| References_xml | – reference: JayaweeraALPakiyarajahDEdussooriyaCUMinimax design of MD sparse FIR filters with arbitrary frequency response using SOCPIEEE Trans Circ Syst II Expr Briefs202269524032407 – reference: GuptaVAn adaptive optimized schizophrenia electroencephalogram disease prediction frameworkWirel Pers Commun202313021191121310.1007/s11277-023-10326-2 – reference: SharmaIPerformance of swarm based optimization techniques for designing digital FIR filter: a comparative studyEng Sci Technol, An Int J201619315641572351821710.1016/j.jestch.2016.05.013 – reference: Yang X-S and Deb S (2010) Engineering optimisation by cuckoo search. arXiv preprint ar Xiv:1005.2908 – reference: GuptaVMittalMMittalVFrWT-PPCA-based R-peak detection for improved management of healthcare systemIETE J Res202110.1080/03772063.2021.1982412 – reference: TsutsumiSSuyamaKDesign of FIR filters with discrete coefficients using ant colony optimizationElectron Commun Jpn2014974303710.1002/ecj.11522 – reference: ArchanaSMahapatraRKPanigrahiSPDEPSO and PSO-QI in digital filter designExpert Syst Appl201138109661097310.1016/j.eswa.2011.02.140 – reference: KarabogaNCetinkayaBIDesign of digital FIR filters using differential evolution algorithmCirc Syst Signal Process2006255649660234392610.1007/s00034-005-0721-7 – reference: Gupta V et al (2023) Adaptive Autoregressive Modeling Based ECG Signal Analysis for Health Monitoring. Optimization Methods for Engineering Problems, Apple Academic Press, pp 1–15 – reference: GuptaVApplication of chaos theory for arrhythmia detection in pathological databasesInt J Med Eng Inform2023152191202 – reference: Chilamkurthi DP, Tirupatipati GC, Sulochanarani J, Pamula VK (2017) Design of optimal digital FIR filters using TLBO and Jaya algorithms. In: International conference on communication and signal processing (ICCSP 2017), pp 0538–0541 – reference: Luitel B, Venayagamoorthy GK (2008) Differential evolution particle swarm optimization for digital filter design. In: IEEE congress on evolutionary computation (IEEE World Congress on Computational Intelligence), pp 3954–3961 – reference: Gupta V, Rathi N (2010) Various objects detection using Bayesian theory. In: Proceedings of the international conference on computer applications II, Pondicherry, India, Research Publishing Services – reference: JiangASparse FIR filter design via partial 1-norm optimizationIEEE Trans Circ Syst II Expr Briefs201967814821486 – reference: AbabnehJIBatainehMHLinear phase FIR filter design using particle swarm optimization and genetic algorithmsDigital Signal Process200818465766810.1016/j.dsp.2007.05.011 – reference: GuptaVECG signal analysis based on the spectrogram and spider monkey optimisation techniqueJ Inst Eng (India) Ser B2023104115316410.1007/s40031-022-00831-6 – reference: KarthickRDesign and analysis of linear phase finite impulse response filter using water strider optimization algorithm in FPGACirc Syst Sig Process20224195254528210.1007/s00034-022-02034-2 – reference: MandalSDesign of optimal linear phase FIR high pass filter using craziness based particle swarm optimization techniqueJ King Saud Univ-Comput Inform Sci20122418392 – reference: Gupta V et al (2021) Nonlinear technique-based ECG signal analysis for improved healthcare systems. In: Proceedings of international conference on communication and computational technologies: ICCCT, Springer Singapore – reference: GuptaVPre-processing based ECG signal analysis using emerging toolsIETE J Res202310.1080/03772063.2023.2202162 – reference: BoudjelabaKRosFChikoucheDAn efficient hybrid genetic algorithm to design finite impulse response filtersExpert Syst Appl201441135917593710.1016/j.eswa.2014.03.034 – reference: Yadav S, Kumar M, Yadav R, Kumar A (2020) A novel approach for optimal digital FIR filter design using hybrid Grey Wolf and Cuckoo search optimization. In: First International Conference on Computing, Communications, and Cyber-Security (IC4S 2019), Springer Singapore, pp 329–343 – reference: SaremiSMirjaliliSLewisAGrasshopper optimisation algorithm: theory and applicationAdv Eng Softw2017105304710.1016/j.advengsoft.2017.01.004 – reference: GuptaVPCA as an effective tool for the detection of R-peaks in an ECG signal processingInt J Syst Assur Eng Manag202213523912403444285210.1007/s13198-022-01650-0 – reference: KumarAKuldeepBDesign of M-channel cosine modulated filter bank using modified Exponential windowJ Franklin Inst2012349313041315289934010.1016/j.jfranklin.2012.01.013 – reference: ReddyKSSahooSKAn approach for FIR filter coefficient optimization using differential evolution algorithmAEU-Int J Electron Commun201569110110810.1016/j.aeue.2014.07.019 – reference: MitraSKDigital signal processing: a computer-based approach2006New YorkMcGraw-Hill Higher Education – reference: PrashanthBUVAhmedMRKounteMRDesign and implementation of DA FIR filter for bio-inspired computing architectureInt J Electr Comput Eng20211121709 – reference: GuptaVMittalMMittalVA novel FrWT based arrhythmia detection in ECG signal using YWARA and PCAWirel Pers Commun202212421229124610.1007/s11277-021-09403-1 – reference: GuptaVAn efficient AR modelling-based electrocardiogram signal analysis for health informaticsInt J Med Eng Inform202214174894439526 – reference: Parks TW and Sidney Burrus C (1987) Digital filter design, Wiley-Interscience – reference: GuptaVDetection of R-peaks using fractional Fourier transform and principal component analysisJ Ambient Intelld Human Comput20221396197210.1007/s12652-021-03484-3 – reference: OliveiraHAPetragliaAPetragliaMRFrequency domain FIR filter design using fuzzy adaptive simulated annealingCirc Syst Sig Process20092889991110.1007/s00034-009-9128-1 – reference: YadavSA novel approach for optimal design of digital FIR filter using grasshopper optimization algorithmISA 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| Title | L1-Norm and LMS Based Digital FIR Filters Design Using Evolutionary Algorithms |
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