ARTIFICIAL NEURAL NETWORKS FOR PATTERN-RECOGNITION

This tutorial article deals with the basics of artificial neural netwo rks (ANN) and their applications in pattern recognition. ANN can be vi ewed as computing models inspired by the structure and function of the biological neural network. These models are expected to deal with pro blem solving in a manner different from conventional computing. A dist inction is made between pattern and data to emphasize the need for dev eloping pattern processing systems to address pattern recognition task s. After introducing the basic principles of ANN, some fundamental net works are examined in detail for their ability to solve simple pattern recognition tasks. These fundamental networks together with the princ iples of ANN will lead to the development of architectures for complex pattern recognition tasks. A few popular architectures are described to illustrate the need to develop an architecture specific to a given pattern recognition problem. Finally several issues that still need to be addressed to solve practical problems using ANN approach are discu ssed.