| Recent studies have indicated that neural networks can be implemented to solve the pattern recognition problem. The formulation of the pattern classification problem by self-organizing neural networks, specifically investigation of the Kohonen neural networks are presented in this work. The Kohonen Topology Preserving Mapping (TPM) network and the Learning Vector Quantization (LVQ) algorithms are reviewed. A formal analysis of the convergence property and the neighborhood interaction function selection in the topology preserving unsupervised neural network are presented. Furthermore, the derivation and convergence of the LVQ algorithms are investigated. A neural network piecewise linear classifier based on the Kohonen LVQ2 algorithm and the Kohonen TPM network is developed. The neural network classifier is tested on both synthesized and real data sets. The performance of the proposed classifier is compared with other neural network classifiers and classical classifiers. |
