Parallel implementation for wavelet dictionary optimization applied to pattern recognition

LEANDRO D. VIGNOLO; DIEGO H. MILONE; HUGO L. RUFINER; ENRIQUE M. ALBORNOZ

Mendoza - Argentina

Congreso; 7th Argentine Symposium on Computing Technology (AST) - 35ta. JAIIO; 2006

By means of full wavelet packet decomposition a redundant set of coefficients is obtained. For signal classification it is convenient to find a subset of these coefficients minimizing the error rate of a classifier. A problem arises because of the computational cost of GA solution. This work presents the parallelization of a genetic algorithm by which it is possible to obtain the best subset of coefficients in order to improve results on phoneme recognition. Various strategies have been evaluated in order to improve the classifier initialization and the evolution itself. Classification results for a set of Spanish phonemes show the advantages of the propossed method and the speedup of the implemented parallelization.