Time series classification using the Volterra connectionist model and Bayes decision theory
J.J. Rajan, Peter Julian Rayner · IEEE International Conference on Acoustics Speech and Signal Processing · 1993
The authors describe the development of a new technique for determining the weights of a Volterra connectionist model (VCM) applied to the classification of stationary time series. This involves assigning a classification index to each class of time series and developing expressions for the state condition probability density functions such that the Bayes risk can be expressed as a function of the weights. The optimal weight values then correspond to the minimum Bayes risk.>