Abstract
Recent times have witnessed a wide application of evolutionary optimization by researchers, in design of digital FIR filters, based on frequency domain specifications. A significant growth has been reported in the field of evolutionary optimization-based FIR filter design. Optimization-based techniques are used to solve the filter design problem by framing the design task as an error function which is further solved to determine the filter coefficients that satisfies the desired specifications. However, the nonlinear, non-differentiable, non-convex, multimodal nature of the associated optimization problem makes the design task quite challenging. In this regard, a number of evolutionary optimization- based techniques have been applied for FIR filter design. This paper provides a comprehensive review of the various evolutionary optimization-based techniques for FIR filter design. In addition to the review, the reported techniques have been analyzed by implementing them on a common platform and comparing them in terms of their effectiveness in meeting the desired specifications.
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References
J.I. Ababneh, M.H. Bataineh, Linear phase FIR filter design using particle swarm optimization and genetic algorithms. Digit. Signal Process. 18, 657–668 (2008). https://doi.org/10.1016/j.dsp.2007.05.011
A. Aggarwal, T.K. Rawat, M. Kumar, D.K. Upadhyay, Design of optimal band-stop FIR filter using L1 norm based RCGA, Ain Shams Eng. J. (2016) Article in press. https://doi.org/10.1016/j.asej.2015.11.022
A. Aggarwal, T.K. Rawat, D.K. Upadhyay, Design of optimal digital FIR filters using evolutionary and swarm optimization techniques. AEU Int. J. Electron. Commun. 70, 373–385 (2015). https://doi.org/10.1016/j.aeue.2015.12.012
A. Aggarwal, M. Kumar, T.K. Rawat, D.K. Upadhyay, Optimal design of 2D FIR filters with quadrantally symmetric properties using fractional derivative constraints. Circuits Syst. Signal Process. 35, 2213–2257 (2016). https://doi.org/10.1007/s00034-016-0283-x
M.K. Ahirwal, A. Kumar, G.K. Singh, Adaptive filtering of EEG/ERP through bounded range artificial bee colony (BR-ABC) algorithm. Digit. Signal Process. A Rev. J. 25, 164–172 (2014). https://doi.org/10.1016/j.dsp.2013.10.019
S.U. Ahmad, A. Antoniou, A genetic algorithm approach for fractional delay FIR filters, in IEEE International Symposium on Circuits and Systems (IEEE, 2006) p. 4. https://doi.org/10.1109/ISCAS.2006.1693135
I. Ahmad, P. Mondal, R. Kanhirodan, A new FIR filter for image restoration, in 1ST IEEE Conference Industrial Electronics Applications (IEEE, 2006) pp. 1–6. https://doi.org/10.1109/ICIEA.2006.257087
C.K. Ahn, A new solution to the induced l \(\infty \) finite impulse response filtering problem based on two matrix inequalities. Int. J. Control 87, 404–409 (2014). https://doi.org/10.1080/00207179.2013.836284
C.K. Ahn, P. Shi, S.H. You, A new approach on design of a digital phase-locked loop. IEEE Signal Process. Lett. 23, 600–604 (2016). https://doi.org/10.1109/LSP.2016.2542291
C.K. Ahn, P. Shi, M.V. Basin, M.V. Basin, Deadbeat dissipative FIR filtering. IEEE Trans. Circuits Syst. I Regul. Pap. 63, 1210–1221 (2016). https://doi.org/10.1109/TCSI.2016.2573281
K. Baderia, A. Kumar, G.Kumar Singh, Hybrid method for designing digital FIR filters based on fractional derivative constraints. ISA Trans. 58, 493–508 (2015). https://doi.org/10.1016/j.isatra.2015.05.015
K. Boudjelaba, F. Ros, D. Chikouche, Potential of particle swarm optimization and genetic algorithms for FIR filter design. Circuits Syst. Signal Process. 33, 3195–3222 (2014). https://doi.org/10.1007/s00034-014-9800-y
K. Boudjelaba, F. Ros, D. Chikouche, Adaptive genetic algorithm-based approach to improve the synthesis of two-dimensional finite impulse response filters. IET Signal Process. 8, 429–446 (2014). https://doi.org/10.1049/iet-spr.2013.0005
C.S. Burrus, J.A. Barreto, I.W. Selesnick, Iterative reweighted least-squares design of FIR filters. IEEE Trans. Signal Process. 42, 2926–2936 (1994). https://doi.org/10.1109/78.330353
L. Cen, Ã. Ling Cen, L. Cen, A hybrid genetic algorithm for the design of FIR filters with SPoT coefficients. Signal Process. 87, 528–540 (2007). https://doi.org/10.1016/j.sigpro.2006.06.015
A. Chandra, S. Chattopadhyay, Performance analysis of DE-optimized multiplier-less finite impulse response data transmission filter, in 5th International Conference on Computer Devices for Communication (IEEE, 2012), pp. 1–4. https://doi.org/10.1109/CODEC.2012.6509216
A. Chandra, S. Chattopadhyay, A new strategy of image denoising using multiplier-less FIR filter designed with the aid of differential evolution algorithm. Multimed. Tools Appl. 75, 1079–1098 (2016). https://doi.org/10.1007/s11042-014-2358-7
A. Chandra, S. Chattopadhyay, B. Ghosh, Design and implementation of SORIGA-optimized powers-of-two FIR Filter on FPGA. AASRI Procedia 9, 51–56 (2014). https://doi.org/10.1016/j.aasri.2014.09.010
S. Chattopadhyay, S.K. Sanyal, A. Chandra, Optimization of control parameters of differential evolution technique for the design of FIR pulse-shaping filter in QPSK modulated system. J. Commun. 6, 558–570 (2011). https://doi.org/10.4304/jcm.6.7.558-570
A.G. Constantinides, W.M. Li, An algebraic approach to the estimation of the order of FIR filters from complete and partial magnitude and phase specifications. IEEE Trans. Signal Process. 55, 1213–1222 (2007). https://doi.org/10.1109/tsp.206.887565
M.A.G. Correa, E. Laciar, Noise removal from EEG signals in polisomnographic records applying adaptive filters in cascade, in Adaptive Filter Application (InTech, 2011) pp. 173–196. https://doi.org/10.5772/17219
S. Dhabal, P. Venkateswaran, A novel accelerated artificial bee colony algorithm for optimal design of two dimensional FIR filter. Multidimens. Syst. Signal Process. 1, 1–23 (2015). https://doi.org/10.1007/s11045-015-0352-5
V. Durbadal, M. Rajib, D. Vasundhara, R. Mandal, S.P.Ghoshal Kar, Digital FIR filter design using fitness based hybrid adaptive differential evolution with particle swarm optimization. Nat. Comput. 13, 55–64 (2014). https://doi.org/10.1007/s11047-013-9381-x
A. Dwivedi, S. Ghosh, N. Londhe, A Modified artificial bee colony optimization based FIR filter design with experimental validation using FPGA. IET Signal Process. (2016). https://doi.org/10.1049/iet-spr.2015.0214
A.K. Dwivedi, S. Ghosh, N.D. Londhe, Bit level FIR filter optimization using hybrid artificial bee colony algorithm, in Annual IEEE India Conference (IEEE, 2015) pp. 1–6. https://doi.org/10.1109/INDICON.2015.7443741
A.K. Dwivedi, S. Ghosh, N.D. Londhe, Low-power FIR filter design using hybrid artificial bee colony algorithm with experimental validation over FPGA, Circuits Syst. Signal Process. 1–31 (2016). https://doi.org/10.1007/s00034-016-0297-4
A.K. Dwivedi, S. Ghosh, N.D. Londhe, Low power 2D finite impulse response filter design using modified artificial bee colony algorithm with experimental validation using field-programmable gate array. IET Sci. Meas. Technol. 10, 671–678 (2016). https://doi.org/10.1049/iet-smt.2016.0069
A.K. Dwivedi, S. Ghosh, N.D. Londhe, Low power FIR filter design using modified multi-objective artificial bee colony algorithm. Eng. Appl. Artif. Intell. 55, 58–69 (2016). https://doi.org/10.1016/j.engappai.2016.06.006
B. Elkarami, M. Ahmadi, An efficient design of 2-D FIR digital filters by using singular value decomposition and genetic algorithm with canonical signed digit (CSD) coefficients, in IEEE 54th International IEEE Midwest Symposium on Circuits and Systems (IEEE, 2011) pp. 1–4. https://doi.org/10.1109/MWSCAS.2011.6026659
O. Franzen, H. Blume, H. Schröder, H. Schro, FIR-filter design with spatial and frequency design constraints using evolution strategies. Signal Process. 68, 295–306 (1998). https://doi.org/10.1016/S0165-1684(98)00079-6
S.P. Ghoshal, S.K. Saha, R. Kar, D. Mandal, Seeker optimisation algorithm: application to the design of linear phase finite impulse response filter. IET Signal Process 6, 763–771 (2012). https://doi.org/10.1049/iet-spr.2011.0353
N. Haridas, E. Elias, Efficient variable bandwidth filters for digital hearing aid using Farrow structure. J. Adv. Res. 7, 255–262 (2016). https://doi.org/10.1016/j.jare.2015.06.002
J. Hua, W. Kuang, Z. Gao, L. Meng, Z. Xu, Image denoising using 2-D FIR filters designed with DEPSO. Multimed. Tools Appl. 69, 157–169 (2014). https://doi.org/10.1007/s11042-012-1263-1
A. Jiang, H.K. Kwan, Y. Zhu, X. Liu, N. Xu, Y. Tang, Design of sparse FIR filters with joint optimization of sparsity and filter order. IEEE Trans. Circuits Syst. I Regul. Pap. 62, 195–204 (2015). https://doi.org/10.1109/TCSI.2014.2354771
N. Karaboga, B. Cetinkaya, Design of digital FIR filters using differential evolution algorithm. Circuits Syst. Signal Process. 25, 649–660 (2006). https://doi.org/10.1007/s00034-005-0721-7
S. Kockanat, N. Karaboga, T. Koza, Image denoising with 2-D FIR filter by using artificial bee colony algorithm, in International Symposium on Innovations in Intelligent Systems and Applications (IEEE, 2012) pp. 1–4. https://doi.org/10.1109/INISTA.2012.6247041
S. Kockanat, N. Karaboga, The design approaches of two-dimensional digital filters based on metaheuristic optimization algorithms: a review of the literature. Artif. Intell. Rev. 44, 265–287 (2015). https://doi.org/10.1007/s10462-014-9427-1
S. Kockanat, N. Karaboga, A novel 2D-ABC adaptive filter algorithm: a comparative study. Digit. Signal Process. 40, 140–153 (2015). https://doi.org/10.1016/j.dsp.2015.02.010
S. Kockanat, N. Karaboga, Medical Image Denoising Using Metaheuristics (Springer, Berlin, 2017). https://doi.org/10.1007/978-3-662-54428-0
T. Kondoh, Y. Nakamura, M. Nishikawa, H. Osawa, Y. Okamoto, Y. Kanai, H. Muraoka, A study on optimal BAR in array head reading, IEEE Trans. Magn. 1–1 (2017). https://doi.org/10.1109/TMAG.2017.2701355
S.R. Kotha, S. Vij, S.K. Sahoo, A study on strategies and Mutant factor in differential evolution algorithm for FIR filter design, in International Conference on Signal Processing and Integrated Networks (IEEE, 2014) pp. 50–55. https://doi.org/10.1109/SPIN.2014.6776920
W. Kuang, J. Hua, Z. Zheng, L. Meng, X. Zhijiang, Frequency sampling design of 2-D FIR filters based on DEPSO, in 8th International Conference on Computing (IEEE, 2012) pp. 1119–1122. https://doi.org/10.1109/ICNC.2012.6234611
F. Latifoğlu, A novel approach to speckle noise filtering based on artificial bee colony algorithm: an ultrasound image application. Comput. Methods Programs Biomed. 111, 561–569 (2013). https://doi.org/10.1016/j.cmpb.2013.05.009
A. Lee, M. Ahmadi, G. Jullien, W.C. Miller, R.S. Lashkari, Digital filter design using genetic algorithm, in IEEE Symposium on Advances in Digital Filtering and Signal Processing Symposium Proceedings (Cat. No.98EX185) (IEEE, 1998) pp. 34–38. https://doi.org/10.1109/ADFSP.1998.685690
G.L.G. Liu, Y.L.Y. Li, G.H.G. He, Design of digital FIR filters using differential evolution algorithm based on reserved genes, in IEEE Congress Evolutionary Computation (IEEE, 2010) pp. 1–7. https://doi.org/10.1109/CEC.2010.5586425
W.-S. Lu, A. Antoniou, Design of digital filters and filter banks by optimization: a state of the art review, in Proceedings of the European Signal Processing Conference, pp. 1–4 (2000)
H.C. Lu, S.T. Tzeng, Design of arbitrary FIR log filters by genetic algorithm approach. Signal Process. 80, 497–505 (2000). https://doi.org/10.1016/S0165-1684(99)00146-2
B. Luitel, G.K. Venayagamoorthy, Differential evolution particle swarm optimization for digital filter design, in IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence, 2008) pp. 3954–3961. https://doi.org/10.1109/CEC.2008.4631335
S. Mandal, S.P. Ghoshal, R. Kar, D. Mandal, Design of optimal linear phase FIR high pass filter using craziness based particle swarm optimization technique. J. King Saud. Univ. Comput. Inf. Sci. 24, 83–92 (2012). https://doi.org/10.1016/j.jksuci.2011.10.007
M. Manosas-Caballu, G. Seco-Granados, A.L. Swindlehurst, Robust beamforming via FIR filtering for GNSS multipath mitigation, in IEEE International Conference on Acoustics, Speech and Signal Processing (IEEE, 2013), pp. 4173–4177. https://doi.org/10.1109/ICASSP.2013.6638445
M. Manuel, E. Elias, Design of multiplier-less FRM FIR filter using artificial bee colony algorithm, in 20th European Conference on Circuit Theory and Design, 5, 322–325 (2011). https://doi.org/10.1109/ECCTD.2011.6043351
M. Manuel, E. Elias, Design of sharp 2D multiplier-less circularly symmetric FIR filter using harmony search algorithm and frequency transformation. J. Signal Inf. Process. 3, 344–351 (2012). https://doi.org/10.4236/jsip.2012.33044
L. Martinez, B. Sarens, C. Glorieux, 2D Finite impulse response filters for surface wave identification, in IEEE International Ultrasonics Symposium (IEEE, 2009) pp. 1598–1601. https://doi.org/10.1109/ULTSYM.2009.5441443
M. Mehendale, M. Road, G. Venkatesh, S.D. Sherlekar, G. Venkatesh, Coefficient optimization for low power realization of FIR filters. VLSI Signal Process. 8, 352–361 (1995). https://doi.org/10.1109/VLSISP.1995.527506
A. Mehrnia, A.N. Willson, FIR filter design using optimal factoring: a walkthrough and summary of benefits. IEEE Circuits Syst. Mag. 16, 8–21 (2016). https://doi.org/10.1109/MCAS.2015.2510178
D. Misra, S. Deb, S. Joardar, Efficient design of quadrature mirror filter bank for audio signal processing using Craziness based Particle Swarm Optimization Technique (2015). https://doi.org/10.1109/IC4.2015.7375563
L. Mitiche, A.B.H. Adamou-Mitiche, An efficient low order model for two-dimensional digital systems: application to the 2D digital filters. J. King Saud. Univ. Comput. Inf. Sci. 26, 308–318 (2014). https://doi.org/10.1016/j.jksuci.2014.03.003
S. Mondal, D. Chakraborty, R. Kar, D. Mandal, S.P. Ghoshal, Novel particle swarm optimization for high pass FIR filter design, in IEEE Symposium on Humanities Science Engneering Research (IEEE, 2012) pp. 413–418. https://doi.org/10.1109/SHUSER.2012.6268874
S. Mondal, S. Prasad, R. Kar, D. Mandal, S.P. Ghoshal, R. Kar, D. Mandal, Differential evolution with wavelet mutation in digital finite impulse response filter design. J. Optim. Theory Appl. 155, 315–324 (2012). https://doi.org/10.1007/s10957-012-0028-3
W.A. Mousa, S. Boussakta, D. McLernon, Realization of 2-D seismic migration FIR digital filters for 3-D seismic volumes via singular value decomposition, in Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (IEEE, 2006) p. II-801–II-804. https://doi.org/10.1109/ICASSP.2006.1660464
M. Najjarzadeh, A. Ayatollahi, FIR digital filters design: particle swarm optimization utilizing LMS and minimax strategies, in IEEE International Symposium on Signal Processing and Information Technology (IEEE, 2008), pp. 129–132. https://doi.org/10.1109/ISSPIT.2008.4775685
S. Narieda, IF signal filtering techniques in low IF receiver for narrowband communications, in IEEE Radio and Wireless Symposium (IEEE, 2013), pp. 94–96. https://doi.org/10.1109/RWS.2013.6486652
S.-H. Ou, K.-C. Chang, C.-W. Liu, An energy-efficient, high-precision SFP LPFIR filter engine for digital hearing aids. Integr. VLSI J. 48, 230–238 (2015). https://doi.org/10.1016/j.vlsi.2014.06.004
M. Pashaian, M.R. Mosavi, M.S. Moghaddasi, M.J. Rezaei, A novel interference rejection method for GPS receivers. Iran. J. Electr. Electron. Eng. 12, 9–20 (2016). https://doi.org/10.22068/IJEEE.12.1.9
J. Radecki, J. Konrad, E. Dubois, Design of multidimensional finite-wordlength FIR and IIR filters by simulated annealing, IEEE Trans. Circuits Syst. II Analog Digit. Signal Process. 42, 424–431 (1995). https://doi.org/10.1109/82.392318
E. Rashedi, A. Zarezadeh, Noise filtering in ultrasound images using gravitational search algorithm, in Iranian Conference on Intelligent Systems (IEEE, 2014), pp. 1–4. https://doi.org/10.1109/IranianCIS.2014.6802559
K.S. Reddy, S.K. Sahoo, An approach for FIR filter coefficient optimization using differential evolution algorithm. AEU Int. J. Electron. Commun. 69, 101–108 (2015). https://doi.org/10.1016/j.aeue.2014.07.019
S.K. Saha, S. Mukherjee, D. Mandal, R. Kar, S.P. Ghoshal, Gravitational search algorithm in digital FIR low pass filter design, in 3rd International Conference on Emerging Applications of Information Technology (2012, 52–55). https://doi.org/10.1109/EAIT.2012.6407860
S.K. Saha, R. Kar, D. Mandal, S.P. Ghoshal, Bacteria foraging optimisation algorithm for optimal FIR filter design. Int. J. Bio-Inspired Comput. 5, 52 (2013). https://doi.org/10.1504/IJBIC.2013.053039
S.K. Saha, S.P. Ghoshal, R. Kar, D. Mandal, S. Kumar, S. Prasad, R. Kar, D. Mandal, S.K. Saha, S.P. Ghoshal, R. Kar, D. Mandal, Cat Swarm Optimization algorithm for optimal linear phase FIR filter design. ISA Trans. 52, 781–794 (2013). https://doi.org/10.1016/j.isatra.2013.07.009
S.K. Saha, R. Dutta, R. Choudhury, R. Kar, D. Mandal, S.P. Ghoshal, Efficient and accurate optimal linear phase FIR filter design using opposition-based harmony search algorithm. Sci. World J. 2013, 1–16 (2013). https://doi.org/10.1155/2013/320489
S. Salcedo-Sanz, F. Cruz-Roldan, C. Heneghan, X.Y.X. Yao, Evolutionary design of digital filters with application to subband coding and data transmission. IEEE Trans. Signal Process. 55, 1193–1203 (2007). https://doi.org/10.1109/TSP.2006.888883
P. Shao, Z. Wu, X. Zhou, D.C. Tran, FIR digital filter design using improved particle swarm optimization based on refraction principle. Soft Comput. (2015). https://doi.org/10.1007/s00500-015-1963-3
M. Shukla, G.R. Mishra, O.P. Singh, S. Kumar, Linear phase digital low pass FIR filter design by attractive and repulsive particle swarm optimization. ACEEE Int. J. Commun. 5, 13–19 (2014)
A.E. Smith, Multi-objective optimization using evolutionary algorithms (Book review). IEEE Trans. Evol. Comput. 6, 526–526 (2002). https://doi.org/10.1109/TEVC.2002.804322
T.J. Su, C.H. Kuo, W.P. Tsai, C.C. Hou, A hybrid of clonal selection algorithm and frequency sampling method for designing a 2-D FIR filter, in Proceedings of the 4th IEEE International Symposium on Electronic Design, Test and Applications, DELTA 2008 (IEEE, 2008) pp. 274–278. https://doi.org/10.1109/DELTA.2008.15
D. Suckley, Genetic algorithm in the design of FIR filters. IEE Proc. Circuits Devices Syst. 138, 234 (1991). https://doi.org/10.1049/ip-g-2.1991.0043
R. Suzutou, Y. Nakamura, M. Nishikawa, H. Osawa, Y. Okamoto, Y. Kanai, H. Muraoka, A study on relationship between recording pattern and decoding reliability in SMR. IEEE Trans. Magn. 1, 1–1 (2017). https://doi.org/10.1109/TMAG.2017.2721428
V. Tirronen, F. Neri, K. Tommi, K. Majava, T. Rossi, An enhanced memetic differential evolution in filter design for defect detection. Evol. Comput. 16, 529–555 (2008). https://doi.org/10.1162/evco.2008.16.4.529
S.T. Tzeng, Genetic algorithm approach for designing 2-D FIR digital filters with 2-D symmetric properties. Signal Process. 84, 1883–1893 (2004). https://doi.org/10.1016/j.sigpro.2004.06.018
S.T. Tzeng, Design of 2-D FIR digital filters with specified magnitude and group delay responses by GA approach. Signal Process. 87, 2036–2044 (2007). https://doi.org/10.1016/j.sigpro.2007.01.034
G. Wade, A. Roberts, G. Williams, Multiplier-less FIR filter design using a genetic algorithm. IEE Proc. Vis. Image Signal Process. 141, 175 (1994). https://doi.org/10.1049/ip-vis:19941185
D. Wei, C.K. Sestok, A.V. Oppenheim, Sparse filter design under a quadratic constraint: low-complexity algorithms. IEEE Trans. Signal Process. 61, 857–870 (2013). https://doi.org/10.1109/TSP.2012.2229996
W. Ye, Y.J. Yu, Greedy algorithm for the design of linear-phase FIR filters with sparse coefficients. Circuits Syst. Signal Process. 35, 1427–1436 (2016). https://doi.org/10.1007/s00034-015-0122-5
S. Zhao, Y.S. Shmaliy, F. Liu, Fast Kalman-like optimal unbiased FIR filtering with applications. IEEE Trans. Signal Process. 64, 2284–2297 (2016). https://doi.org/10.1109/TSP.2016.2516960
R.A. Zitar, A. Al-Dmour, An evolutionary FIR filter design method, in Evolutionary Image Analysis and Signal Processing, ed. by S. Cagnoni (Springer, Berlin, 2009). https://doi.org/10.1007/978-3-642-01636-3_11
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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). https://doi.org/10.1007/s00034-018-0772-1
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DOI: https://doi.org/10.1007/s00034-018-0772-1