DocumentCode
311272
Title
Wavelet packets and genetic algorithms
Author
Astola, Jaakko ; Egiazarian, Karen ; Huttunen, Heikki
Author_Institution
Signal Process. Lab., Tampere Univ. of Technol., Finland
Volume
3
fYear
1997
fDate
21-24 Apr 1997
Firstpage
2117
Abstract
This paper is devoted to the theoretical analysis of the fitness function in genetic algorithms using wavelet packet (WP) transforms. More specifically, WP transforms are used to calculate the average fitness value of a schema. Based on this one can decide whether a certain function is easy or hard for a genetic algorithm. The result is an extension of Bethke´s (1980) work who discovered an efficient method for calculating schema average fitness values using the Walsh transform
Keywords
Walsh functions; filtering theory; genetic algorithms; matrix algebra; transforms; wavelet transforms; Haar transform; Walsh transform; fitness function; genetic algorithms; schema average fitness value; wavelet packet transforms; Algorithm design and analysis; Filter bank; Genetic algorithms; Laboratories; Multiresolution analysis; Signal analysis; Signal processing algorithms; Wavelet analysis; Wavelet packets; Wavelet transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on
Conference_Location
Munich
ISSN
1520-6149
Print_ISBN
0-8186-7919-0
Type
conf
DOI
10.1109/ICASSP.1997.599456
Filename
599456
Link To Document