The history of ANN can be divided into the following three eras в€’ ANN during 1940s to 1960s Output signals, which are produced after combining the input signals and activation rule, may be sent to other units. Each neuron has an internal state, which is called an activation signal. This is the most useful information for neurons to solve a particular problem because the weight usually excites or inhibits the signal that is being communicated. Each connection link is associated with a weight that has information about the input signal. These units, also referred to as nodes or neurons, are simple processors which operate in parallel.Д®very neuron is connected with other neuron through a connection link. ANNs are also named as вЂњartificial neural systems,вЂќ or вЂњparallel distributed processing systems,вЂќ or вЂњconnectionist systems.вЂќ ANN acquires a large collection of units that are interconnected in some pattern to allow communication between the units. What is Artificial Neural Network?ДЄrtificial Neural Network (ANN) is an efficient computing system whose central theme is borrowed from the analogy of biological neural networks. These tasks include pattern recognition and classification, approximation, optimization, and data clustering. The main objective is to develop a system to perform various computational tasks faster than the traditional systems. Neural networks are parallel computing devices, which is basically an attempt to make a computer model of the brain.

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