Editorial: Neural Network Applications

Ingrid Russell

School of Computer Science University of Hartford, Hartford, Connecticut, USA

The last few years have seen great advances in neural network research. In addition, neural networks have shown great promise in a wide variety of application areas. This special issue is devoted to the applications of Neural Networks, with the aim of presenting new and important contributions in this area.

Neural Networks have been applied to a wide variety of application areas and have been shown to be particulary useful in solving problems where traditional artificial intelligence techniques involving symbolic methods have failed or proved inefficient. Such networks have shown promise in problems involving low-level tasks that are computationally intensive, including speech synthesis, pattern recognition, vision, recognition, diagnostic problems, robotic control, computer vision, and many other problems that fall under the category of pattern recognition. Neural networks, with their massive parallelism, can provide the computing power needed for these problems. In addition, rapid advances in hardware technology have diminished some of the limitations experienced earlier by these models.

This special issue aims to bring together papers which present research work on the applications of neural networks. I wish to thank the reviewers who have done an excellent job of ensuring the quality of the accepted papers. I hope that you will find the special issue informative and helpful.


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