State-space central theory based analysis of feedforward neural networks

This paper presents a novel way of analysing feedforward neural networks. The analysis is performed using concepts and theory from state space control theory. Although feedforward neural networks are not strictly dynamic, the theory can be suitably adapted for application to such networks. By considering the concepts in a broad sense, a great deal of information about feedforward neural networks and a better understanding of how feedforward neural networks operate can be obtained.