Neural networks and system identification

Abstract

Neural networks have become a very fashionable area of research with a range of potential applications that spans AI, engineering and science. All the applications are dependent upon training the network with illustrative examples and this involves adjusting the weights which define the strength of connection between the neurons in the network. This can often be interpreted as a system identification problem with the advantage that many of the ideas and results from estimation theory can be applied to provide insight into the neural network problem irrespective of the specific application.