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Dear all, I would like to train a dictionary for vector quantization of LSFs for speech coding. At every iteration, the new centroid is calculated as the arithmetic mean of all the vectors allocated to one cell, if we use Eucledian distance as distortion measure. In the case we use weighted euclidean distance as distortion measure, and the weights are constant, it is easily proved that the centroid is still the arithmetic mean. My question is: what happens when the weights are not constant, but a function of the vector to be quantized? It should be done by minimizing the distortion with respect to the centroid (derivate, equate to zero and solve). Has anybody done the calculation already? Thanks a lot for your help, Giuseppina |
centroid calculation for weighted Euclidian distance
Started by ●June 7, 2001
