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Mesafe ölçümleriyle belirlenen uygunluk fonksiyonunu kullanan yeni bir IIR temelli FIR süzgeç tasarım tekniği

Year 2024, Volume: 39 Issue: 1, 635 - 648, 21.08.2023

Fatma Latifoğlu , Sümeyya Arıkan

https://doi.org/10.17341/gazimmfd.1061112

Abstract

Bu çalışmada, basit ve yeni bir yaklaşımla süzgecin tüm frekans yanıtı parametrelerini kontrol ederek yüksek performanslı bir sonlu dürtü yanıtlı (Finite Impulse Response - FIR) süzgeç tasarım yöntemi geliştirilmiştir. Bu amaçla, geçirme ve durdurma bandı dalgalanmaları, durdurma bandı zayıflaması, geçiş bandı genişliği ve doğrusal faz yanıtı parametrelerinin tamamı göz önünde bulundurularak ve sonsuz dürtü yanıtlı (Infinite Impulse Response - IIR) süzgecin daha iyi frekans yanıtına sahip olma avantajları da kullanılarak IIR süzgeç temelli optimal FIR süzgeç tasarlanmıştır. Butterworth ve Chebyshev süzgeçlerin parametreleri, Yapay Arı Kolonisi (Artificial Bee Colony - ABC) ve Parçacık Sürü Optimizasyonu (Particle Swarm Optimization - PSO) algoritmaları ve çeşitli uzaklık ölçütleri kullanılarak yeni uygunluk fonksiyonlarıyla optimize edilmiştir. Süzgeçlenen işaretler görsel olarak incelendiğinde, önerilen algoritma ile süzgeçlenen işaretin faz gecikmesinin geleneksel süzgeçlere göre daha az olduğu görülmüştür. Ayrıca, tasarlanan süzgecin performansı, dört farklı frekans içeren sinüzoidal bir işareti alt bantlarına ayrıştırmak için test edilmiştir. Sayısal sonuçlara göre, önerilen yaklaşımla tasarlanan süzgeç, işareti diğer yaygın olarak kullanılan geleneksel süzgeçlere göre daha hassas bir şekilde ayrıştırmıştır.

Keywords

FIR süzgeç tasarımı IIR süzgeç optimizasyon algoritmaları

Supporting Institution

Erciyes Üniversitesi Bilimsel Araştırma Projeleri Birimi

Project Number

FDK-2019-8760

Thanks

Bu çalışma Erciyes Üniversitesi Bilimsel Araştırma Projeleri Birimi tarafından FDK-2019-8760 proje numarası ile desteklenmiştir.

References

  • [1] Oppenheim, A.V., Ronald W. S., and John R. B., Discrete-Time Signal Processing, NJ: Prentice Hall, 1999.
  • [2] Najarian K., Splinter R., Biomedical Signal and Image Processing, CRC Press, 2012
  • [3] Proakis J.G., Manolakis D.K., Digital Signal Processing: Principles, Algorithms and Applications, Prentice Hall, 1996 [4] Parks, T. W., and Burrus C.S., Digital Filter Design, New York: John Wiley & Sons, pp. 54–83, 1987.
  • [5] San-José-Revuelta L.M., Arribas J.I., A new approach for the design of digital frequency selective FIR filters using an FPA-based algorithm, Expert Systems With Applications, 106, 92–106, 2018.
  • [6] Joaquim M.B., Lucietto C. A.S., A nearly optimum linear-phase digital FIR filters design, Digital Signal Processing 21, 690–693, 2011
  • [7] Kar R., Mandal D., Mondal S., Ghoshal S.P., Craziness Based Particle Swarm Optimization Algorithm for FIR Band Stop Filter Design, Swarm and Evolutionary Computation, 7, 58–64, 2012
  • [8] Dasha J., Damb B., Swainca R., Design of multipurpose digital FIR double-band filter using hybrid firefly differential evolution algorithm, Applied Soft Computing, 59, 529–545, 2017.
  • [9] Aggarwal A., Rawat T.K., Upadhyay D.K., Design of optimal digital FIR filters using evolutionary and swarm optimization techniques, Int. J. Electron. Commun. (AEÜ) 70, 373–385, 2016.
  • [10] Ababneh J.I., Bataineh M.H., Linear phase FIR filter design using particle swarm optimization and genetic algorithms, Digital Signal Processing 18 657–668, 2008.
  • [11] Apostolov P., Method for FIR filters design with compressed cosine using Chebyshev’snorm, Signal Processing, 91, 2589–2594, 2011
  • [12] Saha S.K., Ghoshal S.P., Kar R., Mandal D., Cat Swarm Optimization algorithm for optimal linear phase FIR filter design, ISA Transactions, 52, 781–794, 2013.
  • [13] Dwivedi A.K., Ghosh S., Londhe N.D., Review and Analysis of Evolutionary Optimization-Based Techniques for FIR Filter Design, Circuits Syst Signal Process, 37,4409–4430, 2018
  • [14] Tsai J.T., Chou J.H., Liu T.K., Optimal design of digital IIR filters by using hybrid Taguchi genetic algorithm, IEEE Transactions on Industrial Electronics, 53, 867–879, 2006
  • [15] Yu Y., Xinjie Y., Cooperative coevolutionary genetic algorithm for digital IIR filter design, IEEE Transactions on Industrial Electronics, 54, 1811–1819, 2007.
  • [16] Kalinli A., Karaboga N., Artificial immune algorithm for IIR filter design, Journal of Engineering Applications of Artificial Intelligence, 18, 919–929, 2005.
  • [17] Vanuytsel G., Boets P., Van Biesen L., Temmerman S., Efficient hybrid optimization of fixed-point cascaded IIR filter coefficients, in: Proc. IEEE Instrumentation and Measurement, May, 793–797, 2002.
  • [18] Wang Y., Li B., Chen Y., Digital IIR filter design using multi-objective optimization evolutionary algorithm, Applied Soft Computing, 11, 1851–1857, 2011
  • [19] Gray, A., The Intuitive Idea of Distance on a Surface, 2nd ed. Boca Raton, FL: CRC Press, 341-345, 1997. [20] Li R., Zhong W. and. Zhu L. , Feature screening via distance correlation learning. Journal of the American Statistical Association, 107(499), 1129-1139, 2012.
  • [21] Melter R.A., Some characterizations of city block distance, Pattern Recognition Letters, 6, 235-240, 1987 [22] Karaboga D., An idea based on honey bee swarm for numerical optimization, Technical Report TR06, Computer Engineering Department, Erciyes University, Turkey,2005.
  • [23] Karaboga N., A new design method based on artificial bee colony algorithm for digital IIR filters, J.Frankl.Inst., 346, 328–348, 2009.
  • [24] J. Kennedy, R.C. Eberhart, Particle swarm optimization, in: Proceedings of IEEE International Conference on Neural Networks, 1942–1948, 1995.
  • [25] Kennedy J., Eberhart R.C., Swarm Intelligence, Morgan Kaufmann, San Francisco, 2001
  • [26] Karaboga N. and Cetinkaya B., Design of Digital FIR Filters using Differential Evolution Algorithm, Circuits Systems Signal Processing, 25(5), 649–660, 2006.
  • [27] Saha, S. K., Kar, R. , Mandal, D. , & Ghoshal, S. P., Bacteria foraging optimization algorithm for optimal FIR filter design, International Journal of Bio-Inspired Computation, 5, 52–66, 2013.
  • [28] Singh, A. P., Design of linear phase low pass fir filter using particle swarm optimization algorithm. International Journal of Computer Applications, 98 (3), 40–44, 2014.
  • [29] https://physionet.org/physiobank/database/nstdb/
  • [30] Moody GB, Muldrow WE, Mark RG., A noise stress test for arrhythmia detectors, Computers in Cardiology; 11:381-384, 1984.
  • [31] Latifoğlu F, A Novel Singular Spectrum Analysis Based Multiobjective Approach For Optımal FIR Filter Design Using Artificial Bee Colony Algorithm, Neural Computing & Applications, 32, 13323–13341, 2020

A novel IIR based FIR filter design technique using a new fitness function determined by distance metrics

Year 2024, Volume: 39 Issue: 1, 635 - 648, 21.08.2023

Fatma Latifoğlu , Sümeyya Arıkan

https://doi.org/10.17341/gazimmfd.1061112

Abstract

Project Number

FDK-2019-8760

References

  • [1] Oppenheim, A.V., Ronald W. S., and John R. B., Discrete-Time Signal Processing, NJ: Prentice Hall, 1999.
  • [2] Najarian K., Splinter R., Biomedical Signal and Image Processing, CRC Press, 2012
  • [3] Proakis J.G., Manolakis D.K., Digital Signal Processing: Principles, Algorithms and Applications, Prentice Hall, 1996 [4] Parks, T. W., and Burrus C.S., Digital Filter Design, New York: John Wiley & Sons, pp. 54–83, 1987.
  • [5] San-José-Revuelta L.M., Arribas J.I., A new approach for the design of digital frequency selective FIR filters using an FPA-based algorithm, Expert Systems With Applications, 106, 92–106, 2018.
  • [6] Joaquim M.B., Lucietto C. A.S., A nearly optimum linear-phase digital FIR filters design, Digital Signal Processing 21, 690–693, 2011
  • [7] Kar R., Mandal D., Mondal S., Ghoshal S.P., Craziness Based Particle Swarm Optimization Algorithm for FIR Band Stop Filter Design, Swarm and Evolutionary Computation, 7, 58–64, 2012
  • [8] Dasha J., Damb B., Swainca R., Design of multipurpose digital FIR double-band filter using hybrid firefly differential evolution algorithm, Applied Soft Computing, 59, 529–545, 2017.
  • [9] Aggarwal A., Rawat T.K., Upadhyay D.K., Design of optimal digital FIR filters using evolutionary and swarm optimization techniques, Int. J. Electron. Commun. (AEÜ) 70, 373–385, 2016.
  • [10] Ababneh J.I., Bataineh M.H., Linear phase FIR filter design using particle swarm optimization and genetic algorithms, Digital Signal Processing 18 657–668, 2008.
  • [11] Apostolov P., Method for FIR filters design with compressed cosine using Chebyshev’snorm, Signal Processing, 91, 2589–2594, 2011
  • [12] Saha S.K., Ghoshal S.P., Kar R., Mandal D., Cat Swarm Optimization algorithm for optimal linear phase FIR filter design, ISA Transactions, 52, 781–794, 2013.
  • [13] Dwivedi A.K., Ghosh S., Londhe N.D., Review and Analysis of Evolutionary Optimization-Based Techniques for FIR Filter Design, Circuits Syst Signal Process, 37,4409–4430, 2018
  • [14] Tsai J.T., Chou J.H., Liu T.K., Optimal design of digital IIR filters by using hybrid Taguchi genetic algorithm, IEEE Transactions on Industrial Electronics, 53, 867–879, 2006
  • [15] Yu Y., Xinjie Y., Cooperative coevolutionary genetic algorithm for digital IIR filter design, IEEE Transactions on Industrial Electronics, 54, 1811–1819, 2007.
  • [16] Kalinli A., Karaboga N., Artificial immune algorithm for IIR filter design, Journal of Engineering Applications of Artificial Intelligence, 18, 919–929, 2005.
  • [17] Vanuytsel G., Boets P., Van Biesen L., Temmerman S., Efficient hybrid optimization of fixed-point cascaded IIR filter coefficients, in: Proc. IEEE Instrumentation and Measurement, May, 793–797, 2002.
  • [18] Wang Y., Li B., Chen Y., Digital IIR filter design using multi-objective optimization evolutionary algorithm, Applied Soft Computing, 11, 1851–1857, 2011
  • [19] Gray, A., The Intuitive Idea of Distance on a Surface, 2nd ed. Boca Raton, FL: CRC Press, 341-345, 1997. [20] Li R., Zhong W. and. Zhu L. , Feature screening via distance correlation learning. Journal of the American Statistical Association, 107(499), 1129-1139, 2012.
  • [21] Melter R.A., Some characterizations of city block distance, Pattern Recognition Letters, 6, 235-240, 1987 [22] Karaboga D., An idea based on honey bee swarm for numerical optimization, Technical Report TR06, Computer Engineering Department, Erciyes University, Turkey,2005.
  • [23] Karaboga N., A new design method based on artificial bee colony algorithm for digital IIR filters, J.Frankl.Inst., 346, 328–348, 2009.
  • [24] J. Kennedy, R.C. Eberhart, Particle swarm optimization, in: Proceedings of IEEE International Conference on Neural Networks, 1942–1948, 1995.
  • [25] Kennedy J., Eberhart R.C., Swarm Intelligence, Morgan Kaufmann, San Francisco, 2001
  • [26] Karaboga N. and Cetinkaya B., Design of Digital FIR Filters using Differential Evolution Algorithm, Circuits Systems Signal Processing, 25(5), 649–660, 2006.
  • [27] Saha, S. K., Kar, R. , Mandal, D. , & Ghoshal, S. P., Bacteria foraging optimization algorithm for optimal FIR filter design, International Journal of Bio-Inspired Computation, 5, 52–66, 2013.
  • [28] Singh, A. P., Design of linear phase low pass fir filter using particle swarm optimization algorithm. International Journal of Computer Applications, 98 (3), 40–44, 2014.
  • [29] https://physionet.org/physiobank/database/nstdb/
  • [30] Moody GB, Muldrow WE, Mark RG., A noise stress test for arrhythmia detectors, Computers in Cardiology; 11:381-384, 1984.
  • [31] Latifoğlu F, A Novel Singular Spectrum Analysis Based Multiobjective Approach For Optımal FIR Filter Design Using Artificial Bee Colony Algorithm, Neural Computing & Applications, 32, 13323–13341, 2020
There are 28 citations in total.

Details

Primary Language Turkish
Subjects Biomedical Engineering (Other)
Journal Section Makaleler
Authors

Fatma Latifoğlu 0000-0003-2018-9616

Sümeyya Arıkan 0000-0001-7582-7537

Project Number FDK-2019-8760
Early Pub Date August 11, 2023
Publication Date August 21, 2023
Submission Date March 25, 2022
Acceptance Date March 25, 2023
Published in Issue Year 2024 Volume: 39 Issue: 1

Cite

APA Latifoğlu, F., & Arıkan, S. (2023). Mesafe ölçümleriyle belirlenen uygunluk fonksiyonunu kullanan yeni bir IIR temelli FIR süzgeç tasarım tekniği. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 39(1), 635-648. https://doi.org/10.17341/gazimmfd.1061112
AMA Latifoğlu F, Arıkan S. Mesafe ölçümleriyle belirlenen uygunluk fonksiyonunu kullanan yeni bir IIR temelli FIR süzgeç tasarım tekniği. GUMMFD. August 2023;39(1):635-648. doi:10.17341/gazimmfd.1061112
Chicago Latifoğlu, Fatma, and Sümeyya Arıkan. “Mesafe ölçümleriyle Belirlenen Uygunluk Fonksiyonunu Kullanan Yeni Bir IIR Temelli FIR süzgeç tasarım tekniği”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 39, no. 1 (August 2023): 635-48. https://doi.org/10.17341/gazimmfd.1061112.
EndNote Latifoğlu F, Arıkan S (August 1, 2023) Mesafe ölçümleriyle belirlenen uygunluk fonksiyonunu kullanan yeni bir IIR temelli FIR süzgeç tasarım tekniği. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 39 1 635–648.
IEEE F. Latifoğlu and S. Arıkan, “Mesafe ölçümleriyle belirlenen uygunluk fonksiyonunu kullanan yeni bir IIR temelli FIR süzgeç tasarım tekniği”, GUMMFD, vol. 39, no. 1, pp. 635–648, 2023, doi: 10.17341/gazimmfd.1061112.
ISNAD Latifoğlu, Fatma - Arıkan, Sümeyya. “Mesafe ölçümleriyle Belirlenen Uygunluk Fonksiyonunu Kullanan Yeni Bir IIR Temelli FIR süzgeç tasarım tekniği”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 39/1 (August 2023), 635-648. https://doi.org/10.17341/gazimmfd.1061112.
JAMA Latifoğlu F, Arıkan S. Mesafe ölçümleriyle belirlenen uygunluk fonksiyonunu kullanan yeni bir IIR temelli FIR süzgeç tasarım tekniği. GUMMFD. 2023;39:635–648.
MLA Latifoğlu, Fatma and Sümeyya Arıkan. “Mesafe ölçümleriyle Belirlenen Uygunluk Fonksiyonunu Kullanan Yeni Bir IIR Temelli FIR süzgeç tasarım tekniği”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, vol. 39, no. 1, 2023, pp. 635-48, doi:10.17341/gazimmfd.1061112.
Vancouver Latifoğlu F, Arıkan S. Mesafe ölçümleriyle belirlenen uygunluk fonksiyonunu kullanan yeni bir IIR temelli FIR süzgeç tasarım tekniği. GUMMFD. 2023;39(1):635-48.