Title :
Wavelet packets and genetic algorithms
Author :
Astola, Jaakko ; Egiazarian, Karen ; Huttunen, Heikki
Author_Institution :
Signal Process. Lab., Tampere Univ. of Technol., Finland
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;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on
Conference_Location :
Munich
Print_ISBN :
0-8186-7919-0
DOI :
10.1109/ICASSP.1997.599456
