Plastic algorithm for adaptive vector quantisation

Abstract

A plastic algorithm for building vector quantisers adaptively attains a dynamic representation of observed data; an unsupervised version of classical crossvalidation rules the algorithm's stopping condition. Combining plasticity with empirical generalisation-based control yields an adaptive methodology for VQ. The paper analyses the method's convergence properties and discusses the model's generalisation performance. Experimental results on synthetic and real, complex testbeds support the model's validity.