Abstract
For the past 40 years or so, interest in the use of (artificial neural networks has been motivated by the recognition that the human brain operates in a manner that is entirely different from a conventional digital computer. A neural network is made up of an interconnection of a large number of nonlinear computation units known as neurons, which operate in a highly parallel fashion. Interest in the use of neural networks was reignited in the 1980s largely due to (1) the popularization of the back-propagation algorithm as a tool for the training of multilayer perceptrons, and (2) the use of attractor neural networks (exemplified by the Hopfield model) as content-addressable memories and optimization networks. For a historical account of neural networks, the reader is referred to Cowan (1990) and Haykin (1994).
Keywords
- Neural Network
- Radial Basis Function Network
- Multilayer Perceptrons
- Neural Information Processing System
- Radar Detection
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Haykin, S. (1994). Intelligent Signal Processing. In: Maldague, X.P.V. (eds) Advances in Signal Processing for Nondestructive Evaluation of Materials. NATO ASI Series, vol 262. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-1056-3_1
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DOI: https://doi.org/10.1007/978-94-011-1056-3_1
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