Cellular Neural Networks and Visual Computing

Foundations and Applications

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Author: Leon O. Chua,Tamas Roska

Publisher: Cambridge University Press

ISBN: 9781139433327

Category: Computers

Page: N.A

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Cellular Nonlinear/neural Network (CNN) technology is both a revolutionary concept and an experimentally proven new computing paradigm. Analogic cellular computers based on CNNs are set to change the way analog signals are processed and are paving the way to an analog computing industry. This unique undergraduate level textbook includes many examples and exercises, including CNN simulator and development software accessible via the Internet. It is an ideal introduction to CNNs and analogic cellular computing for students, researchers and engineers from a wide range of disciplines. Although its prime focus is on visual computing, the concepts and techniques described in the book will be of great interest to those working in other areas of research including modeling of biological, chemical and physical processes. Leon Chua, co-inventor of the CNN, and Tamás Roska are both highly respected pioneers in the field.

Thinking in Complexity

The Computational Dynamics of Matter, Mind, and Mankind

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Author: Klaus Mainzer

Publisher: Springer Science & Business Media

ISBN: 3540722289

Category: Science

Page: 482

View: 2230

This new edition also treats smart materials and artificial life. A new chapter on information and computational dynamics takes up many recent discussions in the community.

Issues in Electronic Circuits, Devices, and Materials: 2011 Edition

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Author: N.A

Publisher: ScholarlyEditions

ISBN: 146496372X

Category: Technology & Engineering

Page: 2452

View: 4240

Issues in Electronic Circuits, Devices, and Materials: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Electronic Circuits, Devices, and Materials. The editors have built Issues in Electronic Circuits, Devices, and Materials: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Electronic Circuits, Devices, and Materials in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Electronic Circuits, Devices, and Materials: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Encyclopedia of Artificial Intelligence

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Author: N.A

Publisher: IGI Global

ISBN: 1599048493

Category: Computers

Page: 1640

View: 7904

"This book is a comprehensive and in-depth reference to the most recent developments in the field covering theoretical developments, techniques, technologies, among others"--Provided by publisher.

Proceedings of the 7th IEEE International Workshop on Cellular Neural Networks and Their Applications

Institute of Applied Physics, Johann Wolfgang Goethe-University, Frankfurt, Germany, 22-24 July, 2002

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Author: Ronald Tetzlaff

Publisher: World Scientific

ISBN: 9789812776792

Category: Computers

Page: 700

View: 8095

This volume covers the fundamental theory of Cellular Neural Networks as well as their applications in various fields such as science and technology. It contains all 83 papers of the 7th International Workshop on Cellular Neural Networks and their Applications. The workshop follows a biennial series of six workshops consecutively hosted in Budapest (1990), Munich, Rome, Seville, London and Catania (2000).

Neural networks in a softcomputing framework

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Author: K.-L. Du,M. N. S. Swamy

Publisher: Springer-Verlag New York Inc

ISBN: 9781846283024

Category: Computers

Page: 566

View: 9153

Conventional model-based data processing methods are computationally expensive and require experts knowledge for the modelling of a system; neural networks provide a model-free, adaptive, parallel-processing solution. Neural Networks in a Softcomputing Framework presents a thorough review of the most popular neural-network methods and their associated techniques.This concise but comprehensive textbook provides a powerful and universal paradigm for information processing. Each chapter provides state-of-the-art descriptions of the important major research results of the respective neural-network methods. A range of relevant computational intelligence topics, such as fuzzy logic and evolutionary algorithms, are introduced. These are powerful tools for neural-network learning. Array signal processing problems are discussed in order to illustrate the applications of each neural-network model.Neural Networks in a Softcomputing Framework is an ideal textbook for graduate students and researchers in this field because in addition to grasping the fundamentals, they can discover the most recent advances in each of the popular models. The systematic survey of each neural-network model and the exhaustive list of references will enable researchers and students to find suitable topics for future research. The important algorithms outlined also make this textbook a valuable reference for scientists and practitioners working in pattern recognition, signal processing, speech and image processing, data analysis and artificial intelligence.

2001 International Semiconductor Conference

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Author: IEEE,National Institute for Research and Development in Microtechnologies,National Institute for Research and Development in Microtechnologies (Romania),Institute of Electrical and Electronics Engineers,National Institute for Research and Development in Microtechnologies (Bucarest),National Institute for Research and Development in Microtechnologies (Romania).

Publisher: IEEE

ISBN: 9780780384996

Category: Semiconductors

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Proceedings

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Author: N.A

Publisher: N.A

ISBN: N.A

Category: Neural networks (Computer science)

Page: N.A

View: 7397