BERNARDINO JÚNIOR, F. M.; http://lattes.cnpq.br/1934903225521860; BERNARDINO JÚNIOR, Francisco Madeiro.
Resumo:
Vector quantization has been widely used as an excellent technique for signal compression,
specially voice and image.
I n this work two techniques for vector quantizers design are presented. The first
technique concerns the introduction of some modifications in Kohonen's neural network
training algorithm. The second concerns the derivation of an algorithm based on
Principal Component Analysis. The performance of each technique is compared to the
performance presented by the traditional LBG algorithm and the superiority of the
proposed algorithms have been evidenced.
For evaluating the great potential and efficiency of vector quantization, results of
simulations of voice signals, images and signals with known distributions are presented.