Artificial Neural Network

Abstract

The long course of evolution has given the human brain many desirable characteristics not present in Von Neumann or modern parallel computers. These include massive parallelism, distributed representation and computation, learning ability, generalization ability,adaptivity, inherent contextual information processing, fault tolerance, and low energy consumption. It is hoped that devices based on biological neural networks will possess some of these desirable characteristics.On this basic we come out with the concept of artificial neural network. An artificial neural network, often just called a neural network, is a mathematical model inspired by biological neural networks. A neural network consists of an interconnected group of artificial neurons, and it processes information using a connectionist approach to computation. Neural networks have emerged in the past few years as an area of unusual opportunity for research, development and application to a variety of real world problems. Indeed, neural networks exhibit characteristics and capabilities not provided by any other technology. The article discusses the motivations behind the development of ANNs and describes the basic biological neuron. This paper presents a brief tutorial on artificial neural networks, some of the most commonly used ANN models and briefly describes several applications of it.