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Pattern Regcognition with Neural Networks covers traditional linear pattern recognition and its nonlinear extension via neural networks from an algorithmic approach. The author has written a real-world practical "why-and-how" text that provides a refreshing contrast to competing texts' thoeretical appraoch and "pie-in-the-sky" claims. The text explores mulitple layered preceptrons and describes network types such as functional link, radial basis function, learning vector quantanization and self-organizing. The author also discusses recent clustering methods. This text is suitable for an advanced undergraduate course in pattern recognition or neural networks, and is also useful as a reference and a resource.


Product details

  • Hardback | 480 pages
  • 197.1 x 241.81 x 26.92mm | 1,020g
  • New York, United States
  • English
  • numerous line figures, tables
  • 0195079205
  • 9780195079203


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