Improved Adaptive Learning Algorithm forConstructive Neural Networks

Abstract

Constructive Neural Network learning algorithms provide incremental ways to determine the near-minimal architecture of a multi layer perceptron network along with learning algorithms for determining appropriate weights for pattern classification problems. An improved version of adaptive learning algorithm in a structured multilayer networks is proposed in this research work. A proper weight setting for the constructive architecture to solve pattern classification problems is analyzed and tabulated.