Physical Models Of Neural Networks

Physical Models Of Neural Networks

By: Tamas Geszti (author)Hardback

Up to 2 WeeksUsually despatched within 2 weeks


This lecture note volume is mainly about the recent development that connected neural network modeling to the theoretical physics of disordered systems. It gives a detailed account of the (Little-) Hopfield model and its ramifications concerning non-orthogonal and hierarchical patterns, short-term memory, time sequences, and dynamical learning algorithms. It also offers a brief introduction to computation in layered feed-forward networks, trained by back-propagation and other methods. Kohonen's self-organizing feature map algorithm is discussed in detail as a physical ordering process. The book offers a minimum complexity guide through the often cumbersome theories developed around the Hopfield model. The physical model for the Kohonen self-organizing feature map algorithm is new, enabling the reader to better understand how and why this fascinating and somewhat mysterious tool works.

Product Details

  • ISBN13: 9789810200121
  • Format: Hardback
  • Number Of Pages: 152
  • ID: 9789810200121
  • ISBN10: 9810200129

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