Abstract

This article introduces the genetic algorithm (GA) as an emerging optimization algorithm for signal processing. After a discussion of traditional optimization techniques, it reviews the fundamental operations of a simple GA and discusses procedures to improve its functionality. The properties of the GA that relate to signal processing are summarized, and a number of applications, such as IIR adaptive filtering, time delay estimation, active noise control, and speech processing, that are being successfully implemented are described.

Keywords

Computer scienceSignal processingGenetic algorithmAlgorithmInfinite impulse responseQuality control and genetic algorithmsNoise (video)Adaptive filterSimple (philosophy)Active noise controlMultidimensional signal processingSpeech processingMeta-optimizationDigital signal processingOptimization problemSpeech recognitionArtificial intelligenceNoise reductionMachine learningDigital filterTelecommunicationsComputer hardware

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Publication Info

Year
1996
Type
article
Volume
13
Issue
6
Pages
22-37
Citations
1089
Access
Closed

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Cite This

K.S. Tang, K.F. Man, Sam Kwong et al. (1996). Genetic algorithms and their applications. IEEE Signal Processing Magazine , 13 (6) , 22-37. https://doi.org/10.1109/79.543973

Identifiers

DOI
10.1109/79.543973