Paper Info
Title
Design of multiplier-less nonuniform filter bank transmultiplexer using genetic algorithm
Abstract
In this paper, the design of multiplier-less nonuniform filter bank transmultiplexer (ML NUFB TMUX) is presented. Coefficient synthesis of the filters in canonic signed digit (CSD) format is modeled as optimization problem and genetic algorithm (GA) is used for the optimization. A new integer chromosome encoding scheme using a look-up table, which is capable of preserving the canonic property of filter coefficients under genetic operations, is introduced. As compared to corresponding binary chromosome encoding scheme, the new encoding scheme has smaller chromosome size, simple encoding and decoding procedure and low computational complexity. New mutation technique and modified crossover technique are introduced to improve the performance of GA. They also enable GA to use the full range of CSD numbers in the look-up table, which is not possible in the binary coded GA. The performance of the proposed algorithm is compared also with simulated annealing (SA) and recently introduced symbol coded GA. Simulation results show that ML NUFB TMUX designed using the proposed algorithm has better performance than that designed using binary coded GA, symbol coded GA and SA. The proposed algorithm is also faster than the binary coded GA, symbol coded GA and SA.
Year
DOI
Venue
2009
10.1016/j.sigpro.2009.05.006
Signal Processing
Keywords
Field
DocType
ml nufb tmux,new mutation technique,simple encoding,genetic algorithm,new encoding scheme,look-up table,corresponding binary chromosome,better performance,proposed algorithm,multiplier-less nonuniform filter bank,new integer chromosome,look up table,genetic operator,frequency response,filter bank,computational complexity,optimization problem,simulated annealing
Simulated annealing,Crossover,Filter bank,Binary code,Algorithm,Decoding methods,Mathematics,Genetic algorithm,Computational complexity theory,Filter design
Journal
Volume
Issue
ISSN
89
11
Signal Processing
Citations 
PageRank 
References 
19
0.89
10
Authors
2
Name
Order
Citations
PageRank
V. J. Manoj1642.59
Elizabeth Elias216817.26