Universality and emergent computation in cellular neural networks /
Cellular computing is a natural information processing paradigm, capable of modeling various biological, physical and social phenomena, as well as other kinds of complex adaptive systems. The programming of a cellular computer is in many respects similar to the genetic evolution in biology, the resu...
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Main Authors: | |
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Corporate Authors: | |
Published: |
World Scientific Pub. Co.,
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Publisher Address: | Singapore ; River Edge, N.J. : |
Publication Dates: | 2003. |
Literature type: | eBook |
Language: | English |
Series: |
World Scientific series on nonlinear science. Series A, Monographs and treatises ;
v. 43 |
Subjects: | |
Online Access: |
http://www.worldscientific.com/worldscibooks/10.1142/5053#t=toc |
Summary: |
Cellular computing is a natural information processing paradigm, capable of modeling various biological, physical and social phenomena, as well as other kinds of complex adaptive systems. The programming of a cellular computer is in many respects similar to the genetic evolution in biology, the result being a proper cell design and a task-specific gene. How should one "program" the cell of a cellular computer such that a dynamic behavior with computational relevance will emerge? What are the "rules" for designing a computationally universal and efficient cell? The answers to those questions can be found in this book. It introduces the relatively new paradigm of the cellular neural network from an original perspective and provides the reader with the guidelines for understanding how such cellular computers can be "programmed" and designed optimally. The book contains numerous practical examples and software simulators, allowing readers to experiment with the various phases of designing cellular computers by themselves. |
Carrier Form: | 1 online resource (xii,247pages) : illustrations (some color). |
Bibliography: | Includes bibliographical references (pages 233-244) and index. |
ISBN: | 9789812564504 (electronic bk.) |
CLC: | TP18 |
Contents: | 1. Introduction. 1.1. Emergent computation as a universal phenomena. 1.2. Emergence. 1.3. Cellular computing systems. 1.4. Universality. 1.5. Designing for emergence, the essence of this book. 1.6. Detecting the potential for emergence: the local activity theory -- 2. Cellular paradigms: theory and simulation. 2.1. Cellular systems. 2.2. Major cellular systems paradigms. 2.3. Matlab simulation of generalized cellular automata. 2.4. Simulation of reaction-diffusion cellular neural networks. 2.5. Concluding remarks -- 3. Universal cells. 3.1. Universality and cellular computation, basic ideas. 3.2. Binary cells. 3.3. Continuous state cells. 3.4. Concluding remarks -- 4. Emergence in continuous-time systems: reaction-diffusion cellular neural networks. 4.1. The theory of local activity as a tool for locating emergent behaviors. 4.2. Narrowing the search, "edge of chaos" domains. 4.3. The methodology of finding "edge of chaos" domains. 4.4. Emergent behaviors within the "edge of chaos" domains of the Brusselator CNN. 4.5. Emergent behaviors within the "edge of chaos" domains of the Gierer-Meinhardt CNN. 4.6. Concluding remarks and engineering perspectives -- 5. Emergence in discrete-time systems: generalized cellular automata. 5.1. Emergent phenomena in binary cellular automata. 5.2. Emergent phenomena in continuous state cellular automata. 5.3. Emergence in coupled generalized cellular automata. 5.4. Concluding remarks -- 6. Unconventional applications: biometric authentication. 6.1. Introduction. 6.2. Generating the stimuli. 6.3. Experimental results. 6.4. Concluding remarks. |