Several industrial and commercial applications of neural network technology have been implemented in recent years. The first neural networks used single-neuron linear networks trained by the LMS algorithm; single-element and multielement linear networks are now used in telecommunications, control of sound and vibration, and particle accelerator beam control. Most current nonlinear multielement neural networks use a backpropagation algorithm, while others use backpropagation-through-time, radial basis functions, genetic algorithms, Kohonen's Learning Vector Quantization, or other algorithms. Most neural network applications can be classified as either pattern classification, prediction and financial analysis, or control and optimization; examples of each are described. Future nonlinear neural network applications are examined.
Source Citation (MLA 8 th Edition)
Widrow, Bernard, et al. "Neural networks: applications in industry, business and science." Communications of the ACM, Mar. 1994, p. 93+. Academic OneFile, Accessed 16 Dec. 2018.
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