The project is about simulations of neural network which is one of the recent developments and survived the great setback before the advent of computer system. Neural networks include many approaches to solve the problem than the computers. Many kinds of neural networks are demonstrated and explained with neural networks application in medicine. The relation between the real and artificial thing is also explained and investigated and ultimately model of mathematics is demonstrated.

 An Artificial Neural Network (ANN) is processing of information of paradigm inspired by methods of nervous systems of biology like brain. The importance of paradigm is the structure of the information processing system consists of interconnected processing neurons to solve problems. ANN is configured for application like data classification or pattern recognition by the process of learning. Biological learning system is the adjustment of the synaptic connections between the neurons.

 There are various advances increased with computer application. This field comes with frustration and disrepute periods including increased resurgence and funding.

The neurophysiologist Warren McCulloch produced the first artificial neuron in 1943. The neural networks are employed to detect trends and extract patterns. There are many advantages of the network. They are adaptive learning, self-organization, real time operation, and fault tolerance by redundant information coding.

Conclusion:

The conclusion made about neural networks is that a lot of things can be gained in the computing world. Things can very powerful and flexible. The network is very best suited for real time systems due to quick response and computational times and parallel architecture.

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