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Neural Network Toolbox for Use with MATLAB
"Neural networks are composed of many simple elements operating in parallel. These elements are inspired by biological nervous systems. The network function is determined largely by the connections between elements. We can train a neural network to perform a particular fune- tion by adjusting the values of the connections between elements.
Neural networks have been trained to perform complex functions in various fields of application including pattern recognition, identifica- tion, classification, speech, vision and control systems. Today neural networks can be trained to solve problems that are difficult for conven- tional computers or human beings..
The field of neural networks has a history of some five decades but has found solid application only in the past twelve years, and the field is still developing rapidly. Thus, it is distinctly different from the fields of con- trol systems or optimization where the terminology, basic mathematics, and design procedures have been firmly established and applied for many years. We do not view the Neural Network Toolbox as simply a summary of established procedures that are known to work well. Rath- er, we hope that it will be a useful tool for industry, education and re- search, a tool that will help users find what works and what doesn't, and a tool that will help develop and extend the field of neural networks. Be- cause the field and the material are so new, this toolbox will explain the procedures, tell how to apply them, and illustrate their successes and failures with examples. We believe that an understanding of the para- digms and their application is essential to the satisfactory and success- ful use of this toolbox, and that without such understanding user complaints and inquiries would bury us. So please be patient if we in- clude a lot of explanatory material. We hope that such material will be helpful to you."
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