Neural and Synergetic Computers

In The cerebral computer - An introduction to the computational structure of ... R. Eckmiller: In Neural Computers, ed. by R. Eckmiller, C. v.d. Malsburg ...

Author: Hermann Haken

Publisher: Springer Science & Business Media

ISBN: 3642741193

Category: Science

Page: 263

View: 794

Neural and Synergetic Computers deals with basic aspect of this rapidly developing field. Several contributions are devoted to the application of basic concepts of synergetics and dynamic systems theory to the constructionof neural computers. Further topics include statistical approaches to neural computers and their design (for example by sparse coding), perception motor control, and new types of spatial multistability in lasers.

Massively Parallel Optical and Neural Computing in Japan

169-185 [ N299 ) Feedback - error - learning neural network for supervised motor learning by : Mitsuo Kawato in : Advanced Neural Computers , ed .

Author: Ulrich Wattenberg

Publisher: IOS Press

ISBN: 9789051990980

Category: Computers

Page: 162

View: 701

A survey of products and research projects in the field of highly parallel, optical and neural computers in Japan. The research activities are listed by type of organization, eg universities and public research organizations, and by industry.


Neural Computers

The 50 contributions in this book cover a wide range of topics, including: Neural Network Architecture, Learning and Memory, Fault Tolerance, Pattern Recognition, and Motor Control in Brains versus Neural Computers.

Author: Rolf Eckmiller

Publisher: Springer Science & Business Media

ISBN: 3642837409

Category: Computers

Page: 566

View: 918

the outcome of a NATO Advanced Research Workshop (ARW) This book is held in Neuss (near Dusseldorf), Federal Republic of Germany from 28 September to 2 October, 1987. The workshop assembled some 50 invited experts from Europe, Ameri ca, and Japan representing the fields of Neuroscience, Computational Neuroscience, Cellular Automata, Artificial Intelligence, and Compu ter Design; more than 20 additional scientists from various countries attended as observers. The 50 contributions in this book cover a wide range of topics, including: Neural Network Architecture, Learning and Memory, Fault Tolerance, Pattern Recognition, and Motor Control in Brains versus Neural Computers. Twelve of these contributions are review papers. The readability of this book was enhanced by a number of measures: * The contributions are arranged in seven chapters. * A separate List of General References helps newcomers to this ra pidly growing field to find introductory books. * The Collection of References from all Contributions provides an alphabetical list of all references quoted in the individual con tributions. * Separate Reference Author and Subject Indices facilitate access to various details. Group Reports (following the seven chapters) summarize the discus sions regarding four specific topics relevant for the 'state of the art' in Neural Computers.

Neural Networks and Soft Computing

Proceedings of the Sixth International Conference on Neural Network and Soft Computing, Zakopane, Poland, June 11-15, 2002 Leszek Rutkowski, Janusz Kacprzyk.

Author: Leszek Rutkowski

Publisher: Springer Science & Business Media

ISBN: 9783790800050

Category: Computers

Page: 914

View: 627

This volume presents new trends and developments in soft computing techniques. Topics include: neural networks, fuzzy systems, evolutionary computation, knowledge discovery, rough sets, and hybrid methods. It also covers various applications of soft computing techniques in economics, mechanics, medicine, automatics and image processing. The book contains contributions from internationally recognized scientists, such as Zadeh, Bubnicki, Pawlak, Amari, Batyrshin, Hirota, Koczy, Kosinski, Novák, S.-Y. Lee, Pedrycz, Raudys, Setiono, Sincak, Strumillo, Takagi, Usui, Wilamowski and Zurada. An excellent overview of soft computing methods and their applications.


Neural Network Computing for the Electric Power Industry

Pao, Y.-l-1., "Applications of Neural-Net Computing to Power Systems" Proceedings of the NSF Workshop on Artificial Neural-Net Methodology in Power System ...

Author: Dejan J. Sobajic

Publisher: Psychology Press

ISBN: 1134781903

Category: Psychology

Page: 240

View: 539

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.


Neural Computing for Advanced Applications

This volume contains the accepted papers presented at the International Conference on Neural Computing for Advanced Applications (NCAA 2020).

Author: Haijun Zhang

Publisher: Springer Nature

ISBN: 981157670X

Category: Application software

Page: 528

View: 624

This book presents refereed proceedings of the First International Conference Neural Computing for Advanced Applications, NCAA 2020, held in July, 2020. Due to the COVID-19 pandemic the conference was held online. The 36 full papers and 7 short papers were thorougly reviewed and selected from a total of 113 qualified submissions. Thes papers present resent research on such topics as neural network theory, and cognitive sciences, machine learning, data mining, data security & privacy protection, and data-driven applications, computational intelligence, nature-inspired optimizers, and their engineering applications, cloud/edge/fog computing, the Internet of Things/Vehicles (IoT/IoV), and their system optimization, control systems, network synchronization, system integration, and industrial artificial intelligence, fuzzy logic, neuro-fuzzy systems, decision making, and their applications in management sciences, computer vision, image processing, and their industrial applications, and natural language processing, machine translation, knowledge graphs, and their applications.

Neural Computing for Optimization and Combinatorics

This book is intended for undergraduate or graduate students, or applied mathematicians/engineers who would like to study neural computing for optimization ...

Author: Yoshiyasu Takefuji

Publisher: World Scientific

ISBN: 9814504483

Category: Science

Page: 244

View: 777

Since Hopfield proposed neural network computing for optimization and combinatorics problems, many neural network investigators have been working on optimization problems. In this book a variety of optimization problems and combinatorics problems are presented by respective experts. A very useful reference book for those who want to solve real-world applications, this book contains applications in graph theory, mathematics, stochastic computing including the multiple relaxation, associative memory and control, resource allocation problems, system identification and dynamic control, and job-stop scheduling. Contents:N-Queen and Crossbar ProblemsGate Packing ProblemsMaximum Clique Problems: Part 1Maximum Clique Problems: Part 2Multi-Layer Channel Routing ProblemsJob-Shop SchedulingBIBD ProblemsDiscovering RNA InteractionsMissionaries and Cannibals ProblemsFunctional Link NetsIdentification and ControlRamsey Numbers Readership: Applied scientists, computer scientists and engineers. keywords:Neural Networks;Combinatorial Optimization;Computation;NP-Hard Problems;Complexity

An Information Theoretic Approach to Neural Computing

An information - theoretic approach to neural computing / Gustavo Deco , Dragan Obradovic . p . cm . Includes bibliographical references and index .

Author: Gustavo Deco

Publisher: Springer Science & Business Media

ISBN: 9780387946665

Category: Computers

Page: 261

View: 130

Neural networks provide a powerful new technology to model and control nonlinear and complex systems. In this book, the authors present a detailed formulation of neural networks from the information-theoretic viewpoint. They show how this perspective provides new insights into the design theory of neural networks. In particular they show 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 several different scientific disciplines, notably cognitive scientists, engineers, physicists, statisticians, and computer scientists, will find this to be a very valuable introduction to this topic.

Advanced Neural Computers

This book is the outcome of the International Symposium on Neural Networks for Sensory and Motor Systems (NSMS) held in March 1990 in the FRG.

Author: R. Eckmiller

Publisher: Elsevier

ISBN: 1483294277

Category: Computers

Page: 464

View: 422

This book is the outcome of the International Symposium on Neural Networks for Sensory and Motor Systems (NSMS) held in March 1990 in the FRG. The NSMS symposium assembled 45 invited experts from Europe, America and Japan representing the fields of Neuroinformatics, Computer Science, Computational Neuroscience, and Neuroscience. As a rapidly-published report on the state of the art in Neural Computing it forms a reference book for future research in this highly interdisciplinary field and should prove useful in the endeavor to transfer concepts of brain function and structure to novel neural computers with adaptive, dynamical neural net topologies. A feature of the book is the completeness of the references provided. An alphabetical list of all references quoted in the papers is given, as well as a separate list of general references to help newcomers to the field. A subject index and author index also facilitate access to various details.

Artificial Neural Networks

( 1988 ) Neural Computers . NATO ASI Series , Series F Computers and Systems Sciences , Vol . 41. Springer - Verlag , Berlin . G.M. Edelman ( 1989 ) Neural ...

Author: P.J. Braspenning

Publisher: Springer Science & Business Media

ISBN: 9783540594888

Category: Computers

Page: 293

View: 143

This book presents carefully revised versions of tutorial lectures given during a School on Artificial Neural Networks for the industrial world held at the University of Limburg in Maastricht, Belgium. The major ANN architectures are discussed to show their powerful possibilities for empirical data analysis, particularly in situations where other methods seem to fail. Theoretical insight is offered by examining the underlying mathematical principles in a detailed, yet clear and illuminating way. Practical experience is provided by discussing several real-world applications in such areas as control, optimization, pattern recognition, software engineering, robotics, operations research, and CAM.

Rough Neural Computing

Exploiting the potential and strength of both neural networks and rough sets, this book is devoted to rough-neuro computing which is also related to the novel aspect of computing based on information granulation, in particular to computing ...

Author: Sankar Kumar Pal

Publisher: Springer Science & Business Media

ISBN: 3642188591

Category: Computers

Page: 736

View: 204

Soft computing comprises various paradigms dedicated to approximately solving real-world problems, e.g. in decision making, classification or learning; among these paradigms are fuzzy sets, rough sets, neural networks, genetic algorithms, and others. It is well understood now in the soft computing community that hybrid approaches combining various paradigms are very promising approaches for solving complex problems. Exploiting the potential and strength of both neural networks and rough sets, this book is devoted to rough-neuro computing which is also related to the novel aspect of computing based on information granulation, in particular to computing with words. It provides foundational and methodological issues as well as applications in various fields.

Artificial Neural Networks for Intelligent Manufacturing

This method of applying artificial neural networks for feature recognition ... REFERENCES Alting, L. and Zhang, H. (1989) Computer aided process planning; ...

Author: C.H. Dagli

Publisher: Springer Science & Business Media

ISBN: 9401107130

Category: Technology & Engineering

Page: 469

View: 872

The quest for building systems that can function automatically has attracted a lot of attention over the centuries and created continuous research activities. As users of these systems we have never been satisfied, and demand more from the artifacts that are designed and manufactured. The current trend is to build autonomous systems that can adapt to changes in their environment. While there is a lot to be done before we reach this point, it is not possible to separate manufacturing systems from this trend. The desire to achieve fully automated manufacturing systems is here to stay. Manufacturing systems of the twenty-first century will demand more flexibility in product design, process planning, scheduling and process control. This may well be achieved through integrated software and hardware archi tectures that generate current decisions based on information collected from manufacturing systems environment, and execute these decisions by converting them into signals transferred through communication network. Manufacturing technology has not yet reached this state. However, the urge for achieving this goal is transferred into the term 'Intelligent Systems' that we started to use more in late 1980s. Knowledge-based systems, our first efforts in this endeavor, were not sufficient to generate the 'Intelligence' required - our quest still continues. Artificial neural network technology is becoming an integral part of intelligent manufacturing systems and will have a profound impact on the design of autonomous engineering systems over the next few years.

Neural Network Parallel Computing

The negative results against the artificial neural network computing had caused less support and interest from governments/industries and consequently ...

Author: Yoshiyasu Takefuji

Publisher: Springer Science & Business Media

ISBN: 1461536421

Category: Technology & Engineering

Page: 230

View: 198

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.

New Trends in Neural Computation

Neural computing is now in progress and the line of future development is uncertain ( 1 ) . The ANN research is largely dependent upon the use of computer ...

Author: International Workshop on Artificial Neural Networks$ (1993 : Sitges, Espagne)

Publisher: Springer Science & Business Media

ISBN: 9783540567981

Category: Computers

Page: 746

View: 412

Neural computation arises from the capacity of nervous tissue to process information and accumulate knowledge in an intelligent manner. Conventional computational machines have encountered enormous difficulties in duplicatingsuch functionalities. This has given rise to the development of Artificial Neural Networks where computation is distributed over a great number of local processing elements with a high degree of connectivityand in which external programming is replaced with supervised and unsupervised learning. The papers presented in this volume are carefully reviewed versions of the talks delivered at the International Workshop on Artificial Neural Networks (IWANN '93) organized by the Universities of Catalonia and the Spanish Open University at Madrid and held at Barcelona, Spain, in June 1993. The 111 papers are organized in seven sections: biological perspectives, mathematical models, learning, self-organizing networks, neural software, hardware implementation, and applications (in five subsections: signal processing and pattern recognition, communications, artificial vision, control and robotics, and other applications).

Pattern Recognition by Self organizing Neural Networks

problems will be solved when , say , optical neural computers , with a vast computing capacity , become feasible . What these people fail to realize is that ...

Author: Gail A. Carpenter

Publisher: MIT Press

ISBN: 9780262031769

Category: Computers

Page: 691

View: 818

Pattern Recognition by Self-Organizing Neural Networks presentsthe most recent advances in an area of research that is becoming vitally important in the fields ofcognitive science, neuroscience, artificial intelligence, and neural networks in general. The 19articles take up developments in competitive learning and computational maps, adaptive resonancetheory, and specialized architectures and biological connections. Introductorysurvey articles provide a framework for understanding the many models involved in various approachesto studying neural networks. These are followed in Part 2 by articles that form the foundation formodels of competitive learning and computational mapping, and recent articles by Kohonen, applyingthem to problems in speech recognition, and by Hecht-Nielsen, applying them to problems in designingadaptive lookup tables. Articles in Part 3 focus on adaptive resonance theory (ART) networks,selforganizing pattern recognition systems whose top-down template feedback signals guarantee theirstable learning in response to arbitrary sequences of input patterns. In Part 4, articles describeembedding ART modules into larger architectures and provide experimental evidence fromneurophysiology, event-related potentials, and psychology that support the prediction that ARTmechanisms exist in the brain. Contributors: J.-P. Banquet, G.A. Carpenter, S.Grossberg, R. Hecht-Nielsen, T. Kohonen, B. Kosko, T.W. Ryan, N.A. Schmajuk, W. Singer, D. Stork, C.von der Malsburg, C.L. Winter.

Neural Computers

The 50 contributions in this book cover a wide range of topics, including: Neural Network Architecture, Learning and Memory, Fault Tolerance, Pattern Recognition, and Motor Control in Brains versus Neural Computers.

Author: Rolf Eckmiller

Publisher:

ISBN: 9783642837418

Category:

Page: 584

View: 162


Hybrid Neural Network and Expert Systems

1.2 Neural Computing The state-of-the-art in neural computing is inspired by our current understanding of biological neural networks; however, after all the ...

Author: Larry R. Medsker

Publisher: Springer Science & Business Media

ISBN: 1461527260

Category: Computers

Page: 240

View: 742

Hybrid Neural Network and Expert Systems presents the basics of expert systems and neural networks, and the important characteristics relevant to the integration of these two technologies. Through case studies of actual working systems, the author demonstrates the use of these hybrid systems in practical situations. Guidelines and models are described to help those who want to develop their own hybrid systems. Neural networks and expert systems together represent two major aspects of human intelligence and therefore are appropriate for integration. Neural networks represent the visual, pattern-recognition types of intelligence, while expert systems represent the logical, reasoning processes. Together, these technologies allow applications to be developed that are more powerful than when each technique is used individually. Hybrid Neural Network and Expert Systems provides frameworks for understanding how the combination of neural networks and expert systems can produce useful hybrid systems, and illustrates the issues and opportunities in this dynamic field.