Neural Networks for Identification, Prediction and Control

by D. T. Pham and Xing Liu

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This publication describes examples of applications of neural networks in modelling, prediction and control. Topics covered include identification of general linear and nonlinear processes, forecasting of river levels, stock market prices, currency exchange rates and control of a time-delayed plant and a two-joint robot. The neural network types considered are the multilayer perceptron (MLP), the Elman and Jordan networks, the Group-Method-of-Data Handling (GMDH), the cerebellar-model-articulation-controller (CMAC) networks and neuromorphic fuzzy logic systems. The algorithms presented are the standard backpropagation (BP) algorithm, the Widrow-Hoff learning, dynamic BP and evolutionary learning. Full listings of computer programmes written in C for neural-network-based system identification and prediction to facilitate practical experimentation with neural network techniques are included.
  • ISBN10 3540199594
  • ISBN13 9783540199595
  • Publish Date 31 May 1995
  • Publish Status Active
  • Out of Print 13 November 2014
  • Publish Country DE
  • Publisher Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
  • Imprint Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Format Hardcover
  • Pages 252
  • Language English