Neural Networks Architectures Design, and Applications: A Review

Abstract

Artificial Neural Networks (ANNs) are modern computing methods that have been used extensively in solving many complicated problems in the physical world. The attractiveness of ANNs stems from its remarkable data processing features, which mainly related to high parallelism, fault and noise resistance, learning and widespread abilities of nonlinearity. This paper introduces a review for some ANNs architectures in the field of recognition, prediction and control to be a useful toolkit and reference for the ANNs modelers. The review mechanism depends on performing a comparison among the newest research in these fields in terms of implemented field, used tools, research technique and significant satisfied aims.