As some physiological presumptions of Brain Learning techniques led to develop Artificial Neural Network ( ANN ) to compete with the Brain's Natural learning phenomenon. Various Networks and Algorithms have been proposed to enhance the machine learning process and to achieve some thing new. In this paper we have proposed a moderate Algorithm for Multivariate Artificial Neural Network.

In the process of learning we may presume the neural networks are simplified models of the biological neurons system. The Artificial Neural Network ( ANN ) is an information processing system which is inspired by brain learning system. It is assumed that brain is composed of a large number of highly interconnected processing elements working in groups to solve specific problems. Various networks and algorithms have been proposed to enhance the machine learning process and to achieve some thing new. In this paper we have proposed a moderate algorithm for most generalized multilevel artificial neural network, which may be reduced to various other forms of neural networks.

We may presume the neural networks are simplified models of the biological neurons system. The Artificial Neural Network (ANN) is an information processing system which is inspired by brain learning system.It is assumed that brain is composed of a large number of highly interconnected processing elements working in groups to solve specific problems. Various networks and algorithms have been proposed to enhance the machine learning process and to achieve some thing new. In this paper we have proposed a moderate algorithm for multistage artificial neural network.

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A radial basis function (RBF) neural network depends mainly upon an adequate choice of the number and positions of its basis function centers. In this paper we have proposed an algorithm for RBF neural network and the results may be reduced for artificial neural networks as particular cases.