Parallel-hierarchical network learning methods and their application to pattern recognition

Abstract

This paper considers provisions necessary for developing parallel-hierarchical network learning methods underlain by the idea of population coding in an artificial neural network and its approximation to natural neural networks. Mathematical parallel-hierarchical network learning models and a combined parallel-hierarchical network learning method are developed for recognizing static and dynamic patterns.