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.