TRAINING AND DEVELOPMENT OFARTIFICIAL NEURAL NETWORK MODELS: SINGLE LAYER FEEDFORWARD AND MULTI LAYER FEEDFORWARD NEURAL NETWORK

Research in the artificial neural network has been attracting and most successful technology in recent years. Though the first model of artificial neurons was presented by Warren McCulloch and Walter Pitts in 1943, the new models have been raised even in the recent years. Some of the problems are so...

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Bibliographic Details
Published in:Journal of Theoretical and Applied Information Technology 2016-02, Vol.84 (2), p.150-150
Main Authors: Pellakuri, Vidyullatha, Rao, D Rajeswara
Format: Article
Language:English
Subjects:
Artificial neural networks
Feedforward
Information technology
Learning
Mathematical models
Neural networks
Neurons
Training
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Summary:Research in the artificial neural network has been attracting and most successful technology in recent years. Though the first model of artificial neurons was presented by Warren McCulloch and Walter Pitts in 1943, the new models have been raised even in the recent years. Some of the problems are solved by mathematical analysis but it leaves many queries openly for further developments. Anyway, the study of neurons, their interconnected nodes and their actions as the brains primary building blocks is one of the most important research fields in modern biology. The purpose of this research article is to provide how to learn the logic behind the architectures, methodologies of artificial neural networks. This study consists of two parts: the first part shows the learning of single layer feed forward neural network architecture, where as in second part the multi layer feed forward back-propagation neural network covers the learning and training of optimization techniques.
ISSN:1817-3195