Pattern recognition by topology free spatio-temporal feature map

Abstract

This paper introduces a novel concept that eliminates the need for a topologically ordered feature map required for a pattern classification task. Spatio-temporal feature maps (Extensions to Kohonen's self-organizing feature maps by a novel concept of selective competition amongst the neurons) have been shown earlier to provide enhanced classification performances over self-organizing feature maps. However, a topologically ordered feature map is still required as a basis to form a spatio-temporal map. In this paper, it is shown that by picking suitable samples of the input patterns as weights and ensuring that the selected weights are stratified and contained within the convex hull of the in..