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Models of Massive Parallelism

Analysis of Cellular Automata and Neural Networks

  • Textbook
  • © 1995

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Authors:
  1. Max Garzon

    1. Department of Mathematical Sciences, The University of Memphis, Memphis, USA

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Table of contents (12 chapters)

  1. Front Matter

    Pages I-XIV
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  2. Turing Computability and Complexity

    • Max Garzon
    Pages 1-15

  3. Cellular Automata

    • Max Garzon
    Pages 17-38

  4. Linear Cellular Automata

    • Max Garzon
    Pages 39-62

  5. Semi-totalistic Automata

    • Max Garzon
    Pages 63-78

  6. Decision Problems

    • Max Garzon
    Pages 79-96

  7. Neural and Random Boolean Networks

    • Max Garzon
    Pages 97-116

  8. General Properties

    • Max Garzon
    Pages 117-139

  9. Classification

    • Max Garzon
    Pages 141-166

  10. Asymptotic Behavior

    • Max Garzon
    Pages 167-198

  11. Some Inverse Problems

    • Old folk
    Pages 199-229

  12. Real Computation

    • Charles P. Baudelaire
    Pages 231-254

  13. A Bibliography of Applications

    • Max Garzon
    Pages 255-262

  14. Back Matter

    Pages 263-274
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Keywords

About this book

Locality is a fundamental restriction in nature. On the other hand, adaptive complex systems, life in particular, exhibit a sense of permanence and time­ lessness amidst relentless constant changes in surrounding environments that make the global properties of the physical world the most important problems in understanding their nature and structure. Thus, much of the differential and integral Calculus deals with the problem of passing from local information (as expressed, for example, by a differential equation, or the contour of a region) to global features of a system's behavior (an equation of growth, or an area). Fundamental laws in the exact sciences seek to express the observable global behavior of physical objects through equations about local interaction of their components, on the assumption that the continuum is the most accurate model of physical reality. Paradoxically, much of modern physics calls for a fundamen­ tal discrete component in our understanding of the physical world. Useful computational models must be eventually constructed in hardware, and as such can only be based on local interaction of simple processing elements.

Authors and Affiliations

  • Department of Mathematical Sciences, The University of Memphis, Memphis, USA

    Max Garzon

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