Neurocomputing
Neurocomputing

Author: James A. Anderson

Publisher: MIT Press

Published: 1993-08-26

Total Pages: 762

ISBN-13: 0262510758

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In bringing together seminal articles on the foundations of research, the first volume of Neurocomputing has become an established guide to the background of concepts employed in this burgeoning field. Neurocomputing 2 collects forty-one articles covering network architecture, neurobiological computation, statistics and pattern classification, and problems and applications that suggest important directions for the evolution of neurocomputing.James A. Anderson is Professor in the Department of Cognitive and Linguistic Sciences at Brown University. Andras Pellionisz is a Research Associate Professor in the Department of Physiology and Biophysics at New York Medical Center and a Senior National Research Council Associate to NASA. Edward Rosenfeld is editor and publisher of the newsletters Intelligence and Medical Intelligence.

Advances in Neural Networks – ISNN 2018
Advances in Neural Networks – ISNN 2018

Author: Tingwen Huang

Publisher: Springer

Published: 2018-05-25

Total Pages: 879

ISBN-13: 3319925377

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This book constitutes the refereed proceedings of the 15th International Symposium on Neural Networks, ISNN 2018, held in Minsk, Belarus in June 2018.The 98 revised regular papers presented in this volume were carefully reviewed and selected from 214 submissions. The papers cover many topics of neural network-related research including intelligent control, neurodynamic analysis, bio-signal, bioinformatics and biomedical engineering, clustering, classification, forecasting, models, algorithms, cognitive computation, machine learning, and optimization.​

Future Directions for Intelligent Systems and Information Sciences
Future Directions for Intelligent Systems and Information Sciences

Author: Nikola Kasabov

Publisher: Springer Science & Business Media

Published: 2000-08-04

Total Pages: 424

ISBN-13: 3790812765

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This edited volume comprises invited chapters that cover five areas of the current and the future development of intelligent systems and information sciences. Half of the chapters were presented as invited talks at the Workshop "Future Directions for Intelligent Systems and Information Sciences" held in Dunedin, New Zealand, 22-23 November 1999 after the International Conference on Neuro-Information Processing (lCONIPI ANZIISI ANNES '99) held in Perth, Australia. In order to make this volume useful for researchers and academics in the broad area of information sciences I invited prominent researchers to submit materials and present their view about future paradigms, future trends and directions. Part I contains chapters on adaptive, evolving, learning systems. These are systems that learn in a life-long, on-line mode and in a changing environment. The first chapter, written by the editor, presents briefly the paradigm of Evolving Connectionist Systems (ECOS) and some of their applications. The chapter by Sung-Bae Cho presents the paradigms of artificial life and evolutionary programming in the context of several applications (mobile robots, adaptive agents of the WWW). The following three chapters written by R.Duro, J.Santos and J.A.Becerra (chapter 3), GCoghill . (chapter 4), Y.Maeda (chapter 5) introduce new techniques for building adaptive, learning robots.

Intercellular Communication
Intercellular Communication

Author: Feliksas Bukauskas

Publisher: Manchester University Press

Published: 1991

Total Pages: 256

ISBN-13: 9780719032691

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(Vocal Score). This revised edition has been prepared from the composer's piano copy rather than the piano-conductor parts so that it can be more useful to the rehearsal pianist. It includes all the scenes and transition parts and a Sondheim bio.

Knowledge-based Neurocomputing
Knowledge-based Neurocomputing

Author: Ian Cloete

Publisher: MIT Press

Published: 2000

Total Pages: 512

ISBN-13: 9780262032742

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Looking at ways to encode prior knowledge and to extract, refine, and revise knowledge within a neurocomputing system.Neurocomputing methods are loosely based on a model of the brain as a network of simple interconnected processing elements corresponding to neurons. These methods derive their power from the collective processing of artificial neurons, the chief advantage being that such systems can learn and adapt to a changing environment. In knowledge-based neurocomputing, the emphasis is on the use and representation of knowledge about an application. Explicit modeling of the knowledge represented by such a system remains a major research topic. The reason is that humans find it difficult to interpret the numeric representation of a neural network.The key assumption of knowledge-based neurocomputing is that knowledge is obtainable from, or can be represented by, a neurocomputing system in a form that humans can understand. That is, the knowledge embedded in the neurocomputing system can also be represented in a symbolic or well-structured form, such as Boolean functions, automata, rules, or other familiar ways. The focus of knowledge-based computing is on methods to encode prior knowledge and to extract, refine, and revise knowledge within a neurocomputing system.ContributorsC. Aldrich, J. Cervenka, I. Cloete, R.A. Cozzio, R. Drossu, J. Fletcher, C.L. Giles, F.S. Gouws, M. Hilario, M. Ishikawa, A. Lozowski, Z. Obradovic, C.W. Omlin, M. Riedmiller, P. Romero, G.P.J. Schmitz, J. Sima, A. Sperduti, M. Spott, J. Weisbrod, J.M. Zurada

Iaeng Transactions On Engineering Sciences: Special Issue For The International Association Of Engineers Conferences 2014
Iaeng Transactions On Engineering Sciences: Special Issue For The International Association Of Engineers Conferences 2014

Author: Sio-iong Ao

Publisher: World Scientific

Published: 2015-03-11

Total Pages: 523

ISBN-13: 9814667374

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Two large international conferences on Advances in Engineering Sciences were held in Hong Kong, March 12-14, 2014, under the International MultiConference of Engineers and Computer Scientists (IMECS 2014), and in London, UK, 2-4 July, 2014, under the World Congress on Engineering 2014 (WCE 2014) respectively. This volume contains 37 revised and extended research articles written by prominent researchers participating in the conferences. Topics covered include engineering mathematics, computer science, electrical engineering, manufacturing engineering, industrial engineering, and industrial applications. The book offers tremendous state-of-the-art advances in engineering sciences and also serves as an excellent reference work for researchers and graduate students working with/on engineering sciences.

Neuro-Computers
Neuro-Computers

Author: K. K. Shukla

Publisher: CRC Press

Published: 2003-01-29

Total Pages: 164

ISBN-13: 9780849317132

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The brain-like architecture of artificial neural networks makes them ideal for tackling problems that are too difficult for conventional architectures, specifically problems that involve pattern recognition or other perceptual tasks. Neuro-Computers: Optimization Based Learning provides an intermediate-level exposition of the exciting world of neuro-computers. It presents the importance of neuro-computing to artificial intelligence, giving historical background and present-day implementation options. The book demonstrates the superiority of the adaptive search strategy over conventional fixed parameter searches performed by backpropagation algorithms. It then explores global optimization strategy and presents genetic algorithms as viable methods to train neuro computers on non-trivial problems. This self-contained volume is delivered in a format that is suitable for graduate students, as well as researchers who want to begin work in neuro-computing or related artificial intelligence applications.