NDLI: Optimal linear phase fir high pass filter design using PSOCFIWA-WM

Content Provider	IEEE Xplore Digital Library
Author	Saha, S.K. Kar, R. Mandai, T.I. Kumar, N. Ghoshal, S.P.
Copyright Year	2012
Description	Author affiliation: Department of Electrical Engg., National Institute of Technology, Durgapur, India (Kumar, N.; Ghoshal, S.P.) \|\| Dept of Electronic; and Communication Engg., National Institute of Technology, Durgapur, India (Saha, S.K.; Kar, R.; Mandai, T.I.)
Abstract	In this paper, an optimal design of linear phase digital high pass (HP) finite impulse response (FIR) filter has been proposed using Particle Swarm Optimization with Constriction Factor and Inertia Weight Approach and Wavelet Mutation (PSOCFIWA-WM). PSOCFIWA-WM incorporates a new definition of swarm updating in PSOCFIWA with the help of wavelet based mutation. Wavelet mutation enhances the PSOCFIWA to explore the solution space more effectively. In the design process, filter length, pass band and stop band edge frequencies, feasible pass band and stop band ripple sizes are specified. Other evolutionary algorithms like real coded genetic algorithm (RGA), particle swarm optimization (PSO), PSO with constriction factor and inertia weight approach (PSOCFIWA), and the proposed PSOCFIWA-WM have been used for the comparative design of linear phase FIR HP filter. A comparison of simulation results reveals the optimization superiority of the proposed technique over the other optimization techniques for the solution of FIR HP filter design.
Starting Page	768
Ending Page	773
File Size	337026
Page Count	6
File Format	PDF
ISBN	9781467348065
e-ISBN	9781467348058
DOI	10.1109/WICT.2012.6409178
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-30
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Decision support systems Wavelet Mutation FIR Filter High Pass Filier Communications technology Evolutionary Optimization
Content Type	Text
Resource Type	Article

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