A fast robust stochastic algorithm for vector quantizer design for nonstationary channels

Presents the development of the RGSKAε, a new algorithm for designing vector quantizers. The main features of this algorithm are the following: due to its stochastic nature it avoids being trapped in poor local minima; initial codebook is not needed; the codevectors move away from the gravity centre of the training vectors towards their final position; source coding and channel coding are jointly optimized to obtain a codebook robust against different levels of the transmission noise; The resulted codebook always performs as well or even better than existing codebooks designed for noisy or noiseless channels; the computational complexity is only slightly higher than that of the most widely used K-means algorithm; the bootstrap sampling technique can be successfully applied in case of a large training set; the method is suitable for parallel implementation