The Identification Of Cellular Automata
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Author | : Andrew I. Adamatzky |
Publisher | : CRC Press |
Total Pages | : 384 |
Release | : 1994-11-25 |
Genre | : Science |
ISBN | : 9780748401727 |
This book presents the foundation and development of the theory of cellular automata identification and its application to natural systems. It first sets out the known and proposes the new classes of cellular automata. Numerous examples are included for ease of understanding. It then deals with the designs of algorithms for cellular automata identification. Conceptual questions of automata theory are next addressed and the focus is shifted from synthesis to analysis and from pronostication to accurate factorization. Finally, the author discusses a number of naturally occuring specific instances with a view to expanding and transforming current ideas on cellular automata practice.
Author | : Andrew I. Adamatzky |
Publisher | : CRC Press |
Total Pages | : 384 |
Release | : 1994-11-30 |
Genre | : Science |
ISBN | : 9780748401734 |
This book presents the foundation and development of the theory of cellular automata identification and its application to natural systems. It first sets out the known and proposes the new classes of cellular automata. Numerous examples are included for ease of understanding. It then deals with the designs of algorithms for cellular automata identification. Conceptual questions of automata theory are next addressed and the focus is shifted from synthesis to analysis and from pronostication to accurate factorization. Finally, the author discusses a number of naturally occuring specific instances with a view to expanding and transforming current ideas on cellular automata practice.
Author | : Y. Zhao |
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Total Pages | : |
Release | : 2006 |
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Author | : Sheng Song Mei |
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Total Pages | : |
Release | : 2005 |
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Author | : Yifan Zhao |
Publisher | : |
Total Pages | : |
Release | : 2006 |
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Author | : Burton H. Voorhees |
Publisher | : World Scientific |
Total Pages | : 287 |
Release | : 1996 |
Genre | : Mathematics |
ISBN | : 9810222211 |
Cellular automata provide one of the most interesting avenues into the study of complex systems in general, as well as having an intrinsic interest of their own. Because of their mathematical simplicity and representational robustness they have been used to model economic, political, biological, ecological, chemical, and physical systems. Almost any system which can be treated in terms of a discrete representation space in which the dynamics is based on local interaction rules can be modelled by a cellular automata.The aim of this book is to give an introduction to the analysis of cellular automata (CA) in terms of an approach in which CA rules are viewed as elements of a nonlinear operator algebra, which can be expressed in component form much as ordinary vectors are in vector algebra. Although a variety of different topics are covered, this viewpoint provides the underlying theme. The actual mathematics used is not hard, and the material should be accessible to anyone with a junior level university background, and a certain degree of mathematical maturity.
Author | : Karl-Peter Hadeler |
Publisher | : Springer |
Total Pages | : 467 |
Release | : 2017-05-27 |
Genre | : Mathematics |
ISBN | : 3319530437 |
This book provides an overview of the main approaches used to analyze the dynamics of cellular automata. Cellular automata are an indispensable tool in mathematical modeling. In contrast to classical modeling approaches like partial differential equations, cellular automata are relatively easy to simulate but difficult to analyze. In this book we present a review of approaches and theories that allow the reader to understand the behavior of cellular automata beyond simulations. The first part consists of an introduction to cellular automata on Cayley graphs, and their characterization via the fundamental Cutis-Hedlund-Lyndon theorems in the context of various topological concepts (Cantor, Besicovitch and Weyl topology). The second part focuses on classification results: What classification follows from topological concepts (Hurley classification), Lyapunov stability (Gilman classification), and the theory of formal languages and grammars (Kůrka classification)? These classifications suggest that cellular automata be clustered, similar to the classification of partial differential equations into hyperbolic, parabolic and elliptic equations. This part of the book culminates in the question of whether the properties of cellular automata are decidable. Surjectivity and injectivity are examined, and the seminal Garden of Eden theorems are discussed. In turn, the third part focuses on the analysis of cellular automata that inherit distinct properties, often based on mathematical modeling of biological, physical or chemical systems. Linearity is a concept that allows us to define self-similar limit sets. Models for particle motion show how to bridge the gap between cellular automata and partial differential equations (HPP model and ultradiscrete limit). Pattern formation is related to linear cellular automata, to the Bar-Yam model for the Turing pattern, and Greenberg-Hastings automata for excitable media. In addition, models for sand piles, the dynamics of infectious d
Author | : Kendall Preston Jr. |
Publisher | : Springer Science & Business Media |
Total Pages | : 354 |
Release | : 2013-06-29 |
Genre | : Computers |
ISBN | : 1489903933 |
It is with great pleasure that I present this fourth vol ume in the series "Advanced Applications in Pattern Recognition." It would be difficult to find two authors better versed in the design and application of parallel image processing systems, due to both their own many years of pioneering in the field and their encyclopedic knowledge of what is going on in uni versity and industrial laboratories around the world. The monograph is unique in its parallel presentation of orthogonal and hexagonal dissections, and the wealth of graphic illustration of algorithmic procedures for processing and analyz ing images in the various known implementations of parallel im age-processing architectures. This volume should find a place on the bookshelf of every practitioner of pattern recognition, image processing, and compu ter graphics. Morton Nadler General Editor vii PREFACE This book endeavors to introduce the reader to the subject of cellular logic and cellular automata and is devoted particu larly to those parts dealing with the manipulation of pictorial data. The study of cellular automata owes much to the pioneer ing work of John von Neumann during the 1950s. Von Neumann was interested in general problems in the behavior of computing structures and was immensely impressed by the complexity and performance of the human brain, which he felt must point to wards successful designs for automatic computing machines.
Author | : Burton Voorhees |
Publisher | : World Scientific |
Total Pages | : 287 |
Release | : 1995-12-31 |
Genre | : Science |
ISBN | : 9814500585 |
Cellular automata provide one of the most interesting avenues into the study of complex systems in general, as well as having an intrinsic interest of their own. Because of their mathematical simplicity and representational robustness they have been used to model economic, political, biological, ecological, chemical, and physical systems. Almost any system which can be treated in terms of a discrete representation space in which the dynamics is based on local interaction rules can be modelled by a cellular automata.The aim of this book is to give an introduction to the analysis of cellular automata (CA) in terms of an approach in which CA rules are viewed as elements of a nonlinear operator algebra, which can be expressed in component form much as ordinary vectors are in vector algebra. Although a variety of different topics are covered, this viewpoint provides the underlying theme. The actual mathematics used is not hard, and the material should be accessible to anyone with a junior level university background, and a certain degree of mathematical maturity.
Author | : Howard Gutowitz |
Publisher | : MIT Press |
Total Pages | : 510 |
Release | : 1991 |
Genre | : Computers |
ISBN | : 9780262570862 |
The thirty four contributions in this book cover many aspects of contemporary studies on cellular automata and include reviews, research reports, and guides to recent literature and available software. Cellular automata, dynamic systems in which space and time are discrete, are yielding interesting applications in both the physical and natural sciences. The thirty four contributions in this book cover many aspects of contemporary studies on cellular automata and include reviews, research reports, and guides to recent literature and available software. Chapters cover mathematical analysis, the structure of the space of cellular automata, learning rules with specified properties: cellular automata in biology, physics, chemistry, and computation theory; and generalizations of cellular automata in neural nets, Boolean nets, and coupled map lattices.Current work on cellular automata may be viewed as revolving around two central and closely related problems: the forward problem and the inverse problem. The forward problem concerns the description of properties of given cellular automata. Properties considered include reversibility, invariants, criticality, fractal dimension, and computational power. The role of cellular automata in computation theory is seen as a particularly exciting venue for exploring parallel computers as theoretical and practical tools in mathematical physics. The inverse problem, an area of study gaining prominence particularly in the natural sciences, involves designing rules that possess specified properties or perform specified task. A long-term goal is to develop a set of techniques that can find a rule or set of rules that can reproduce quantitative observations of a physical system. Studies of the inverse problem take up the organization and structure of the set of automata, in particular the parameterization of the space of cellular automata. Optimization and learning techniques, like the genetic algorithm and adaptive stochastic cellular automata are applied to find cellular automaton rules that model such physical phenomena as crystal growth or perform such adaptive-learning tasks as balancing an inverted pole.Howard Gutowitz is Collaborateur in the Service de Physique du Solide et Résonance Magnetique, Commissariat a I'Energie Atomique, Saclay, France.