Unsupervised pattern classification by means of cellular neural networks
Giovanni Costantini, Daniele Casali, Massimo Carota · 2005
Abstract:- A novel algorithm for unsupervised classification of datasets made up of integer valued patterns by means of Cellular Neural Network (CNN) is proposed. The adopted CNN is n-dimensional and is based on a space-variant template-neighborhood order 1- to cluster n-dimensional datasets. The choice of a CNN architecture allows a straightforward hardware implementation, particularly suited for bi-dimensional patterns.