Artificial Neural Network

Artificial Neural Network

ABSTRACT:

An Artificial Neural Network (ANN) is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. Neural network simulations appear to be a recent development. However, this field was established before the advent of computers.

This report is an introduction to ANN. The various types of ANN are explained and demonstrated giving emphasis on Neural Networks vs Conventional Computers. This paper also describes the analogy between the ANN and the brain, and presents the architecture of Neural Networks.

Finally it depicts various fields in which the ANN is presently being employed
Effectively and successfully, including research areas such as neurology and psychology.

The ‘Last but not least’ exciting aspect of Neural Networks is the possibility that some day ‘Conscious’ networks might be produced. In fact there are a number of scientists arguing that the ‘conscious’ neural networks are a realistic possibility.

Introduction:

What is a Neural Network?

An Artificial Neural Network (ANN) is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. ANNs, like people, learn by example. An ANN is configured for a specific application, such as pattern recognition or data classification, through a learning process. Learning in biological systems involves adjustments to the synaptic connections that exist between the neurons. This is true of ANNs as well.


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