NDLI: Adaptive genetic algorithm-based approach to improve the synthesis of two-dimensional finite impulse response filters

Content Provider	IET Digital Library
Author	Boudjelaba, Kamal Ros, Frédéric Chikouche, Djamel
Abstract	The design of finite impulse response (FIR) filters can be formulated as a non-linear optimization problem reputed to be difficult for conventional approaches. The constraints are high and a large number of parameters have to be estimated, especially when dealing with two-dimensional FIR filters. In order to improve the performance of conventional approaches, the authors explore several stochastic methodologies capable of handling large spaces. The authors specifically propose a new genetic algorithm (GA) in which some innovative concepts are introduced to improve the convergence and make its use easier for practitioners. The algorithm is globally improved by adapting the mutation and crossover and selection operators with the genetic advances. A dynamic ranking selection scheme is introduced to limit the promotion of extraordinary chromosomes. A refreshing mechanism is investigated to manage the trade-off between diversity and elitism. The key point of the proposed approach stems from the capacity of the GA to adapt the genetic operators during the genetic life while remaining simple and easy to implement. Most of the parameters and operators are changed by the GA itself. From an initial calibration, the GA performs the design problem while calibrating and repeatedly re-calibrating itself for solving it. The authors demonstrate on various cases of filter design a significant improvement in performance.
Starting Page	429
Ending Page	446
Page Count	18
ISSN	17519675
Volume Number	8
e-ISSN	17519683
Issue Number	Issue 5, Jul (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/8/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2013.0005
Journal	IET Signal Processing
Publisher Date	2013-10-24
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	2D Finite Impulse Response Filters 2D FIR Filters Adaptive Genetic Algorithm-based Approach Convergence Improvement Crossover Operator Digital Signal Processing Dynamic Ranking Selection Scheme Filtering Method in Signal Processing FIR Filter Genetic Algorithm Genetic Life Mutation Operator Nonlinear Optimization Problem Nonlinear Programming Optimisation Technique Selection Operator Signal Processing Theory Two Dimensional Digital Filter
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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