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Radial Basis Function and Neural Networks

Manali B. Mahajan, Dr. J. S. Awati


In the paper, artificial neural networks and their various concepts in pattern recognition and signal have explain. Demand for Neural network is increasing in coming days so that interconnection between neuron to neuron is visualized effectively and it is directly related to the human brain contributing nervous system. Neural Network is a optimized problem solving technique The paper will demonstrate the Artificial Neural Network using SPSS 16.0 software. The paper will discuss the input layers, output layers and hidden layers and also interconnection of them. By observing the neural information obtained in results the paper will design a model. Designing of Neural Network in SPSS 16.0 is easier to understand so that neural paper will be convenient to design. In the paper Radial Basis Function is used to design a Neural Network. Radial Basis Function (RBF) is a hierarchy based way to design a Neural Network. Upper layer, lower layer concepts are included in the Radial Basis Function. The paper will be working on Artificial Neural Network (ANN) and will obtain a solution to the engineering problem.

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