Kr. Muller et al., ANALYSIS OF SWITCHING DYNAMICS WITH COMPETING NEURAL NETWORKS, IEICE transactions on fundamentals of electronics, communications and computer science, E78A(10), 1995, pp. 1306-1315
Citations number
NO
Categorie Soggetti
Engineering, Eletrical & Electronic","Computer Science Hardware & Architecture","Computer Science Information Systems
We present a framework for the unsupervised segmentation of time serie
s. It applies to non-stationary signals originating from different dyn
amical systems which alternate in time, a phenomenon which appears in
many natural systems. In our approach, predictors compete for data poi
nts of a given time series. We combine competition and evolutionary in
ertia to a learning rule. Under this learning rule the system evolves
such that the predictors, which finally survive, unambiguously identif
y the underlying processes. The segmentation achieved by this method i
s very precise and transients are included, a fact, which makes our ap
proach promising for future applications.