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Self-Organization and Associative Memory

  • Textbook
  • © 1988

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Part of the book series: Springer Series in Information Sciences (SSINF, volume 8)

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Table of contents (10 chapters)

Keywords

About this book

Two significant things have happened since the writing of the first edition in 1983. One of them is recent arousal of strong interest in general aspects of "neural computing", or "neural networks", as the previous neural models are nowadays called. The incentive, of course, has been to develop new com­ puters. Especially it may have been felt that the so-called fifth-generation computers, based on conventional logic programming, do not yet contain in­ formation processing principles of the same type as those encountered in the brain. All new ideas for the "neural computers" are, of course, welcome. On the other hand, it is not very easy to see what kind of restrictions there exist to their implementation. In order to approach this problem systematically, cer­ tain lines of thought, disciplines, and criteria should be followed. It is the pur­ pose of the added Chapter 9 to reflect upon such problems from a general point of view. Another important thing is a boom of new hardware technologies for dis­ tributed associative memories, especially high-density semiconductor circuits, and optical materials and components. The era is very close when the parallel processors can be made all-optical. Several working associative memory archi­ tectures, based solely on optical technologies, have been constructed in recent years. For this reason it was felt necessary to include a separate chapter (Chap. 10) which deals with the optical associative memories. Part of its con­ tents is taken over from the first edition.

Authors and Affiliations

  • Laboratory of Computer and Information Sciences, Helsinki University of Technology, Espoo 15, Finland

    Teuvo Kohonen

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