Nonlinear System Identification

Nonlinear System Identification
Author: Stephen A. Billings
Publisher: John Wiley & Sons
Total Pages: 611
Release: 2013-09-23
Genre: Technology & Engineering
ISBN: 1119943590

Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains describes a comprehensive framework for the identification and analysis of nonlinear dynamic systems in the time, frequency, and spatio-temporal domains. This book is written with an emphasis on making the algorithms accessible so that they can be applied and used in practice. Includes coverage of: The NARMAX (nonlinear autoregressive moving average with exogenous inputs) model The orthogonal least squares algorithm that allows models to be built term by term where the error reduction ratio reveals the percentage contribution of each model term Statistical and qualitative model validation methods that can be applied to any model class Generalised frequency response functions which provide significant insight into nonlinear behaviours A completely new class of filters that can move, split, spread, and focus energy The response spectrum map and the study of sub harmonic and severely nonlinear systems Algorithms that can track rapid time variation in both linear and nonlinear systems The important class of spatio-temporal systems that evolve over both space and time Many case study examples from modelling space weather, through identification of a model of the visual processing system of fruit flies, to tracking causality in EEG data are all included to demonstrate how easily the methods can be applied in practice and to show the insight that the algorithms reveal even for complex systems NARMAX algorithms provide a fundamentally different approach to nonlinear system identification and signal processing for nonlinear systems. NARMAX methods provide models that are transparent, which can easily be analysed, and which can be used to solve real problems. This book is intended for graduates, postgraduates and researchers in the sciences and engineering, and also for users from other fields who have collected data and who wish to identify models to help to understand the dynamics of their systems.

Identification Of Cellular Automata

Identification Of Cellular Automata
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.

Modern Cellular Automata

Modern Cellular Automata
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.

Cellular Automata Transforms

Cellular Automata Transforms
Author: Olurinde Lafe
Publisher: Springer Science & Business Media
Total Pages: 181
Release: 2012-12-06
Genre: Computers
ISBN: 1461543657

Cellular Automata Transforms describes a new approach to using the dynamical system, popularly known as cellular automata (CA), as a tool for conducting transforms on data. Cellular automata have generated a great deal of interest since the early 1960s when John Conway created the `Game of Life'. This book takes a more serious look at CA by describing methods by which information building blocks, called basis functions (or bases), can be generated from the evolving states. These information blocks can then be used to construct any data. A typical dynamical system such as CA tend to involve an infinite possibilities of rules that define the inherent elements, neighborhood size, shape, number of states, and modes of association, etc. To be able to build these building blocks an elegant method had to be developed to address a large subset of these rules. A new formula, which allows for the definition a large subset of possible rules, is described in the book. The robustness of this formula allows searching of the CA rule space in order to develop applications for multimedia compression, data encryption and process modeling. Cellular Automata Transforms is divided into two parts. In Part I the fundamentals of cellular automata, including the history and traditional applications are outlined. The challenges faced in using CA to solve practical problems are described. The basic theory behind Cellular Automata Transforms (CAT) is developed in this part of the book. Techniques by which the evolving states of a cellular automaton can be converted into information building blocks are taught. The methods (including fast convolutions) by which forward and inverse transforms of any data can be achieved are also presented. Part II contains a description of applications of CAT. Chapter 4 describes digital image compression, audio compression and synthetic audio generation, three approaches for compressing video data. Chapter 5 contains both symmetric and public-key implementation of CAT encryption. Possible methods of attack are also outlined. Chapter 6 looks at process modeling by solving differential and integral equations. Examples are drawn from physics and fluid dynamics.

Identification Of Cellular Automata

Identification Of Cellular Automata
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.

Parallel Computing: Software Technology, Algorithms, Architectures & Applications

Parallel Computing: Software Technology, Algorithms, Architectures & Applications
Author: Gerhard Joubert
Publisher: Elsevier
Total Pages: 975
Release: 2004-09-23
Genre: Computers
ISBN: 0080538436

Advances in Parallel Computing series presents the theory and use of of parallel computer systems, including vector, pipeline, array, fifth and future generation computers and neural computers. This volume features original research work, as well as accounts on practical experience with and techniques for the use of parallel computers.

Cellular Automata: Analysis and Applications

Cellular Automata: Analysis and Applications
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