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Neural Networks

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Intelligent Systems for Engineering

Abstract

Within recent years, neural networks, also referred to as parallel distributed processing systems or connectionist systems, have experienced a resurgence of interest (the first surge occurred in the 1960s) as a paradigm of computation and knowledge representation. The increase in interest in this “new” area of artificial intelligence (AI) is illustrated by the number of research and application papers appearing in conferences concerning neural networks ([36], [37], and [38]). Neural networks, as the name implies, are loosely modelled after the biological structure of the brain. A neural network is constructed from a set of simple processing units, each capable only of a few computations such as summation and threshold logic. The power gained by a neural network is that there are many of these processors and that each processor is connected to many others, in much the same way that the neurons in our brain are highly interconnected.

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  1. Manufacturing Systems Integration Division Manufacturing Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, 20899-0001, USA

    Dr. Ram D. Sriram

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Sriram, R.D. (1997). Neural Networks. In: Intelligent Systems for Engineering. Springer, London. https://doi.org/10.1007/978-1-4471-0631-9_8

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  • DOI: https://doi.org/10.1007/978-1-4471-0631-9_8

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