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Author : Ramachandran Bharath
Publisher : TAB/Electronics
ISBN 13 : 9780070051454
Total Pages : 188 pages
Book Rating : 4.0/5 (514 download)
Download or read book Neural Network Computing written by Ramachandran Bharath and published by TAB/Electronics. This book was released on 1994-01-01 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Yoshiyasu Takefuji
Publisher : Springer Science & Business Media
ISBN 13 : 1461536421
Total Pages : 237 pages
Book Rating : 4.4/5 (615 download)
Download or read book Neural Network Parallel Computing written by Yoshiyasu Takefuji and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural Network Parallel Computing is the first book available to the professional market on neural network computing for optimization problems. This introductory book is not only for the novice reader, but for experts in a variety of areas including parallel computing, neural network computing, computer science, communications, graph theory, computer aided design for VLSI circuits, molecular biology, management science, and operations research. The goal of the book is to facilitate an understanding as to the uses of neural network models in real-world applications. Neural Network Parallel Computing presents a major breakthrough in science and a variety of engineering fields. The computational power of neural network computing is demonstrated by solving numerous problems such as N-queen, crossbar switch scheduling, four-coloring and k-colorability, graph planarization and channel routing, RNA secondary structure prediction, knight's tour, spare allocation, sorting and searching, and tiling. Neural Network Parallel Computing is an excellent reference for researchers in all areas covered by the book. Furthermore, the text may be used in a senior or graduate level course on the topic.
Author : R Beale
Publisher : CRC Press
ISBN 13 : 9781420050431
Total Pages : 260 pages
Book Rating : 4.0/5 (54 download)
Download or read book Neural Computing - An Introduction written by R Beale and published by CRC Press. This book was released on 1990-01-01 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural computing is one of the most interesting and rapidly growing areas of research, attracting researchers from a wide variety of scientific disciplines. Starting from the basics, Neural Computing covers all the major approaches, putting each in perspective in terms of their capabilities, advantages, and disadvantages. The book also highlights the applications of each approach and explores the relationships among models developed and between the brain and its function. A comprehensive and comprehensible introduction to the subject, this book is ideal for undergraduates in computer science, physicists, communications engineers, workers involved in artificial intelligence, biologists, psychologists, and physiologists.
Author : Ramachandran Bharath
Publisher : McGraw-Hill Companies
ISBN 13 :
Total Pages : 212 pages
Book Rating : 4.3/5 (97 download)
Download or read book Neural Network Computing written by Ramachandran Bharath and published by McGraw-Hill Companies. This book was released on 1994 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to neural networking for systems designers, software developers, programmers, and advanced hobbyists. The authors explain how "brain-style" computing will revolutionize information processing in the 21st century. The disk includes programs for simulating artificial neural networks.
Author : Robert Kozma
Publisher : Academic Press
ISBN 13 : 0323958168
Total Pages : 398 pages
Book Rating : 4.3/5 (239 download)
Download or read book Artificial Intelligence in the Age of Neural Networks and Brain Computing written by Robert Kozma and published by Academic Press. This book was released on 2023-10-27 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. The book covers the major basic ideas of "brain-like computing" behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters. Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN Authored by top experts, global field pioneers, and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making Edited by high-level academics and researchers in intelligent systems and neural networks Includes all new chapters, including topics such as Frontiers in Recurrent Neural Network Research; Big Science, Team Science, Open Science for Neuroscience; A Model-Based Approach for Bridging Scales of Cortical Activity; A Cognitive Architecture for Object Recognition in Video; How Brain Architecture Leads to Abstract Thought; Deep Learning-Based Speech Separation and Advances in AI, Neural Networks
Author : Alianna J. Maren
Publisher : Academic Press
ISBN 13 : 148326484X
Total Pages : 472 pages
Book Rating : 4.4/5 (832 download)
Download or read book Handbook of Neural Computing Applications written by Alianna J. Maren and published by Academic Press. This book was released on 2014-05-10 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Neural Computing Applications is a collection of articles that deals with neural networks. Some papers review the biology of neural networks, their type and function (structure, dynamics, and learning) and compare a back-propagating perceptron with a Boltzmann machine, or a Hopfield network with a Brain-State-in-a-Box network. Other papers deal with specific neural network types, and also on selecting, configuring, and implementing neural networks. Other papers address specific applications including neurocontrol for the benefit of control engineers and for neural networks researchers. Other applications involve signal processing, spatio-temporal pattern recognition, medical diagnoses, fault diagnoses, robotics, business, data communications, data compression, and adaptive man-machine systems. One paper describes data compression and dimensionality reduction methods that have characteristics, such as high compression ratios to facilitate data storage, strong discrimination of novel data from baseline, rapid operation for software and hardware, as well as the ability to recognized loss of data during compression or reconstruction. The collection can prove helpful for programmers, computer engineers, computer technicians, and computer instructors dealing with many aspects of computers related to programming, hardware interface, networking, engineering or design.
Author : Dejan J. Sobajic
Publisher : Psychology Press
ISBN 13 : 1134781970
Total Pages : 246 pages
Book Rating : 4.1/5 (347 download)
Download or read book Neural Network Computing for the Electric Power Industry written by Dejan J. Sobajic and published by Psychology Press. This book was released on 2013-06-17 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Power system computing with neural networks is one of the fastest growing fields in the history of power system engineering. Since 1988, a considerable amount of work has been done in investigating computing capabilities of neural networks and understanding their relevance to providing efficient solutions for outstanding complex problems of the electric power industry. A principal objective of a power utility is to provide electric energy to its customers in a secure, reliable and economic manner. Toward this aim, utility personnel are engaged in a variety of activities in areas of supervisory control and monitoring, evaluation of operating conditions, operation planning and scheduling, system development, equipment testing, etc. Over the past decades significant advances have been made in the development of new concepts, design of hardware and software systems, and implementation of solid-state devices which all contributed to the steadily improving power system performance that we are experiencing today. Advanced information processing technologies played an important role in these development efforts. Members of the Special Interest Group for Power Engineering of the INNS recognized the need for bringing together leading researchers in the field of neurocomputing with experts from power utilities and manufacturing companies to assess the current state of affairs and to explore the directions of further research and practice. This book is based on The Summer Workshop on Neural Network Computing for the Electric Power Industry which brought together approximately forty specialists with backgrounds in power engineering, system operation and planning, neural network theory and AI systems design. An informal and highly inspiring atmosphere of the workshop facilitated open discussion and exchange of expertise between the participants.
Author : Xingui He
Publisher : Springer Science & Business Media
ISBN 13 : 3540737626
Total Pages : 240 pages
Book Rating : 4.5/5 (47 download)
Download or read book Process Neural Networks written by Xingui He and published by Springer Science & Business Media. This book was released on 2010-07-05 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the first time, this book sets forth the concept and model for a process neural network. You’ll discover how a process neural network expands the mapping relationship between the input and output of traditional neural networks and greatly enhances the expression capability of artificial neural networks. Detailed illustrations help you visualize information processing flow and the mapping relationship between inputs and outputs.
Author : Lionel Tarassenko
Publisher : Elsevier
ISBN 13 : 0080512607
Total Pages : 151 pages
Book Rating : 4.0/5 (85 download)
Download or read book Guide to Neural Computing Applications written by Lionel Tarassenko and published by Elsevier. This book was released on 1998-01-30 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks have shown enormous potential for commercial exploitation over the last few years but it is easy to overestimate their capabilities. A few simple algorithms will learn relationships between cause and effect or organise large volumes of data into orderly and informative patterns but they cannot solve every problem and consequently their application must be chosen carefully and appropriately. This book outlines how best to make use of neural networks. It enables newcomers to the technology to construct robust and meaningful non-linear models and classifiers and benefits the more experienced practitioner who, through over familiarity, might otherwise be inclined to jump to unwarranted conclusions. The book is an invaluable resource not only for those in industry who are interested in neural computing solutions, but also for final year undergraduates or graduate students who are working on neural computing projects. It provides advice which will help make the best use of the growing number of commercial and public domain neural network software products, freeing the specialist from dependence upon external consultants.
Author : Philip D. Wasserman
Publisher : Van Nostrand Reinhold Company
ISBN 13 :
Total Pages : 280 pages
Book Rating : 4.3/5 (91 download)
Download or read book Advanced Methods in Neural Computing written by Philip D. Wasserman and published by Van Nostrand Reinhold Company. This book was released on 1993 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the engineer's guide to artificial neural networks, the advanced computing innovation which is posed to sweep into the world of business and industry. The author presents the basic principles and advanced concepts by means of high-performance paradigms which function effectively in real-world situations.
Author : Igor Aleksander
Publisher :
ISBN 13 :
Total Pages : 322 pages
Book Rating : 4.3/5 (91 download)
Download or read book An Introduction to Neural Computing written by Igor Aleksander and published by . This book was released on 1995 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of this text has been updated and includes material on new developments including neurocontrol, pattern analysis and dynamic systems. The book should be useful for undergraduate students of neural networks.
Author :
Publisher :
ISBN 13 :
Total Pages : 136 pages
Book Rating : 4.:/5 (31 download)
Download or read book Journal of Neural Network Computing written by and published by . This book was released on 1991 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : John R. Koza
Publisher : MIT Press
ISBN 13 : 9780262111706
Total Pages : 856 pages
Book Rating : 4.1/5 (117 download)
Download or read book Genetic Programming written by John R. Koza and published by MIT Press. This book was released on 1992 with total page 856 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic programming may be more powerful than neural networks and other machine learning techniques, able to solve problems in a wider range of disciplines. In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic Programming contains a great many worked examples and includes a sample computer code that will allow readers to run their own programs.In getting computers to solve problems without being explicitly programmed, Koza stresses two points: that seemingly different problems from a variety of fields can be reformulated as problems of program induction, and that the recently developed genetic programming paradigm provides a way to search the space of possible computer programs for a highly fit individual computer program to solve the problems of program induction. Good programs are found by evolving them in a computer against a fitness measure instead of by sitting down and writing them.
Author : Sun-Chong Wang
Publisher : Springer Science & Business Media
ISBN 13 : 1461503779
Total Pages : 268 pages
Book Rating : 4.4/5 (615 download)
Download or read book Interdisciplinary Computing in Java Programming written by Sun-Chong Wang and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Books on computation in the marketplace tend to discuss the topics within specific fields. Many computational algorithms, however, share common roots. Great advantages emerge if numerical methodologies break the boundaries and find their uses across disciplines. Interdisciplinary Computing In Java Programming Language introduces readers of different backgrounds to the beauty of the selected algorithms. Serious quantitative researchers, writing customized codes for computation, enjoy cracking source codes as opposed to the black-box approach. Most C and Fortran programs, despite being slightly faster in program execution, lack built-in support for plotting and graphical user interface. This book selects Java as the platform where source codes are developed and applications are run, helping readers/users best appreciate the fun of computation. Interdisciplinary Computing In Java Programming Language is designed to meet the needs of a professional audience composed of practitioners and researchers in science and technology. This book is also suitable for senior undergraduate and graduate-level students in computer science, as a secondary text.
Author : Igor Aleksander
Publisher : Van Nostrand Reinhold Company
ISBN 13 :
Total Pages : 276 pages
Book Rating : 4.3/5 (91 download)
Download or read book An Introduction to Neural Computing written by Igor Aleksander and published by Van Nostrand Reinhold Company. This book was released on 1990 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of this text has been updated and includes material on new developments including neurocontrol, pattern analysis and dynamic systems. The book should be useful for undergraduate students of neural networks.
Author : Gustavo Deco
Publisher : Springer Science & Business Media
ISBN 13 : 1461240166
Total Pages : 265 pages
Book Rating : 4.4/5 (612 download)
Download or read book An Information-Theoretic Approach to Neural Computing written by Gustavo Deco and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: A detailed formulation of neural networks from the information-theoretic viewpoint. The authors show how this perspective provides new insights into the design theory of neural networks. In particular they demonstrate how these methods may be applied to the topics of supervised and unsupervised learning, including feature extraction, linear and non-linear independent component analysis, and Boltzmann machines. Readers are assumed to have a basic understanding of neural networks, but all the relevant concepts from information theory are carefully introduced and explained. Consequently, readers from varied scientific disciplines, notably cognitive scientists, engineers, physicists, statisticians, and computer scientists, will find this an extremely valuable introduction to this topic.
Author : Dejan Sobajic
Publisher :
ISBN 13 :
Total Pages : 240 pages
Book Rating : 4.:/5 (11 download)
Download or read book Neural Network Computing for the Electric Power Industry written by Dejan Sobajic and published by . This book was released on 2013 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Power system computing with neural networks is one of the fastest growing fields in the history of power system engineering. Since 1988, a considerable amount of work has been done in investigating computing capabilities of neural networks and understanding their relevance to providing efficient solutions for outstanding complex problems of the electric power industry. A principal objective of a power utility is to provide electric energy to its customers in a secure, reliable and economic manner. Toward this aim, utility personnel are engaged in a variety of activities in areas of supervisory control and monitoring, evaluation of operating conditions, operation planning and scheduling, system development, equipment testing, etc. Over the past decades significant advances have been made in the development of new concepts, design of hardware and software systems, and implementation of solid-state devices which all contributed to the steadily improving power system performance that we are experiencing today. Advanced information processing technologies played an important role in these development efforts. Members of the Special Interest Group for Power Engineering of the INNS recognized the need for bringing together leading researchers in the field of neurocomputing with experts from power utilities and manufacturing companies to assess the current state of affairs and to explore the directions of further research and practice. This book is based on The Summer Workshop on Neural Network Computing for the Electric Power Industry which brought together approximately forty specialists with backgrounds in power engineering, system operation and planning, neural network theory and AI systems design. An informal and highly inspiring atmosphere of the workshop facilitated open discussion and exchange of expertise between the participants.
