Uma alternativa de acelera？？o do algoritmo fuzzy K-Means aplicado à quantiza？？o vetorial

signal compression, digital watermarking and pattern recognition are examples of applications of vector quantization (vq). a relevant problem concerning vq is codebook design. in this paper, an alternative is presented for accelerating the fuzzy k-it means algorithm applied to codebook design. simulation results involving vq of images and gauss-markov signals show that the proposed method leads to an increase of convergence speed (reduction of the number of iterations) of the fuzzy k-it means algorithm without sacrificing the quality of the designed codebooks.