Discrete vector quantization for arbitrary distance function estimation

The Time Adaptive Self Organizing Map for Distribution Estimation

The feature map represented by the set of weight vectors of the basic SOM (Self-Organizing Map) provides a good approximation to the input space from which the sample vectors come. But the timedecreasing learning rate and neighborhood function of the basic SOM algorithm reduce its capability to adapt weights for a varied environment. In dealing with non-stationary input distributions and changi...

Vector Quantization for Arbitrary Distance Function Estimation

| In this paper we apply the concepts of Vector Quantization (VQ) for the determination of arbitrary distance functions { a problem which has important applications in Logistics and Location Analysis. The input to our problem is the set of coordinates of a large number of nodes whose inter-node arbitrary \distances" have to be estimated. To render the problem interesting, non-trivial and realis...

Relevance-Vector-Machine Quantization and Density-Function Estimation: Application to HMM-Based Multi-Aspect Target Classification

The relevance vector machine (RVM) is applied for feature-vector quantization (codebook design) and for density-function estimation in high-dimensional feature space. The RVM represents a Bayesian extension of the widely applied support vector machine (SVM). The use of RVMs for quantization and density-function estimation is explored with application to discrete and continuous HMMs, respectivel...

Exploiting acoustic feature correlations by joint neural vector quantizer design in a discrete HMM system

In previous work about hybrid speech recognizers with discrete HMMs we have shown that VQs, that are trained according to an MMI criterion, are well suited for ML estimated Bayes classifiers. This is only valid for single VQ systems. In this paper we extend the theory to speech recognizers with multiple VQs. This leads to a joint training criterion for arbitrary multiple neural VQs that conside...

Distributed Video Coding (DVC): Motion estimation and DCT quantization in low complexity video compression