NDLI: Linear phase low pass FIR filter design using Genetic Particle Swarm Optimization with dynamically varying neighbourhood technique

Content Provider	IEEE Xplore Digital Library
Author	Ghosh, Avishek Ghosh, Arnab Chowdhury, Arkabandhu Konar, Amit Eunjin Kim Nagar, Atulya K.
Copyright Year	2012
Description	Author affiliation: Department of Computer Science, John D. Odegard School of Aerospace Sciences, University of North Dakota, Grand Forks, 58202-9015, USA (Eunjin Kim) \|\| Department of Electronics and Tele-communication Engineering, Jadavpur University, Kolkata-700032, India (Ghosh, Avishek; Ghosh, Arnab; Chowdhury, Arkabandhu; Konar, Amit) \|\| Department of Math and Computer Science, Liverpool Hope University, UK (Nagar, Atulya K.)
Abstract	The paper presents an elegant approach for designing linear phase low pass digital FIR filter using swarm and evolutionary algorithms. Classical gradient based approaches are not efficient enough for accurate design and thus evolutionary approach is considered to be a better choice. In this paper a hybrid of Genetic Algorithm and Particle Swarm Optimization algorithm with varying neighbourhood topology, namely Genetic Lbest Particle Swarm Optimization with Dynamically Varying Neighbourhood (GLPSO DVN) is used to find the filter coefficients. In this work two objective functions (error metrics) are minimized. The first one is based on stop and pass band ripple and the second one studies the mean square error between the ideal and actual designed filter. The hybrid algorithm is found to produce fitter candidate solution than the classical Lbest PSO. The results are compared with the results obtained by solving the same problem using Lbest PSO (LPSO). It is also observed that GLPSO DVN gives better results than LPSO and as well LPSO DVN.
Starting Page	1
Ending Page	7
File Size	976115
Page Count	7
File Format	PDF
ISBN	9781467315104
e-ISBN	9781467315098
e-ISBN	9781467315081
DOI	10.1109/CEC.2012.6256176
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-10
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Finite impulse response filter IIR filters Filtering algorithms Transversal filters Band pass filters Passband Llbest PSO Genetic Algorithm crossover mutation Digital filters Low pass filters
Content Type	Text
Resource Type	Article

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