Handbook Of Neural Computation

Author : Pijush Samui,Sanjiban Sekhar Roy,Valentina E. Balas
Publisher : Academic Press
Page : 658 pages
File Size : 44,9 Mb
Release : 2017-07-18
Category : Technology & Engineering
ISBN : 9780128113196

Get Book

Handbook of Neural Computation by Pijush Samui,Sanjiban Sekhar Roy,Valentina E. Balas Pdf

Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations, such as data prediction, classification of images, analysis of big data, and intelligent decision-making, this book provides readers with the latest, cutting-edge research in one comprehensive text. Features high-quality research articles on multivariate adaptive regression splines, the minimax probability machine, and more Discusses machine learning techniques, including classification, clustering, regression, web mining, information retrieval and natural language processing Covers supervised, unsupervised, reinforced, ensemble, and nature-inspired learning methods

Author : Pijush Samui,Sanjiban Sekhar Roy,Valentina E. Balas
Publisher : Academic Press
Page : 600 pages
File Size : 41,6 Mb
Release : 2017-07-28
Category : Electronic
ISBN : 0128113189

Get Book

Handbook of Neural Computation by Pijush Samui,Sanjiban Sekhar Roy,Valentina E. Balas Pdf

Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering to electronics, electrical engineering, and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing, and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations such as data prediction, classification of images, analysis of big data, and intelligent decision making, Handbook of Neural Computation provides readers with the latest, cutting-edge research in one comprehensive text. Features high-quality research articles on multivariate adaptive regression splines, the minimax probability machine, Bayesian networks, Gaussian process regression, as well as support, relevance, and least square support vector machines Discusses machine learning techniques including classification, clustering, regression, web mining, information retrieval, and natural language processing Covers supervised, unsupervised, reinforced, ensemble, and nature-inspired learning methods

Author : Alianna J. Maren,Craig T. Harston,Robert M. Pap
Publisher : Academic Press
Page : 472 pages
File Size : 52,8 Mb
Release : 2014-05-10
Category : Computers
ISBN : 9781483264844

Get Book

Handbook of Neural Computing Applications by Alianna J. Maren,Craig T. Harston,Robert M. Pap Pdf

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 : E Fiesler,R Beale
Publisher : CRC Press
Page : 436 pages
File Size : 49,6 Mb
Release : 1996-01-01
Category : Mathematics
ISBN : 0750303123

Get Book

Handbook of Neural Computation by E Fiesler,R Beale Pdf

The Handbook of Neural Computation is a practical, hands-on guide to the design and implementation of neural networks used by scientists and engineers to tackle difficult and/or time-consuming problems. The handbook bridges an information pathway between scientists and engineers in different disciplines who apply neural networks to similar problems. It is unmatched in the breadth of its coverage and is certain to become the standard reference resource for the neural network community.

Author : Anonim
Publisher : Unknown
Page : 128 pages
File Size : 45,8 Mb
Release : 1997
Category : Neural networks (Computer science)
ISBN : 0750304146

Get Book

Handbook of Neural Computation by Anonim Pdf

Author : Michael A. Arbib
Publisher : MIT Press
Page : 1328 pages
File Size : 48,8 Mb
Release : 2003
Category : Neural circuitry
ISBN : 9780262011976

Get Book

The Handbook of Brain Theory and Neural Networks by Michael A. Arbib Pdf

This second edition presents the enormous progress made in recent years in the many subfields related to the two great questions : how does the brain work? and, How can we build intelligent machines? This second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. (Midwest).

Author : Emile Fiesler,Russell Beale
Publisher : CRC Press
Page : 120 pages
File Size : 51,5 Mb
Release : 1997-01-01
Category : Technology & Engineering
ISBN : 075030524X

Get Book

Handbook of Neural Computation by Emile Fiesler,Russell Beale Pdf

In recent years, neural computation has developed from a specialized research discipline into a broadly based and dynamic activity with applications in an astonishing variety of fields. Many scientists, engineers and other practitioners are now using neural networks to tackle problems that are either intractable or unrealistically time consuming to solve through traditional computational strategies. The inaugural volume in the Computational Intelligence Library provides speedy dissemination of new ideas to a broad spectrum of neural network users, designers and implementers. Devoted to network fundamentals, models, algorithms and applications, the work is intended to become the standard reference resource for the neural network community. As the field expands and develops, leading researchers will report on an analyze promising new approaches. In this way, the Handbook will become an evolving compendium on the state of the art of neural computation. Available in loose-leaf print form as well as in an electronic edition that combines both CD-ROM and on-line (World Wide Web) access to its contents, the Handbook of Neural Computation is available on a subscription basis, with regularly published supplements keeping readers abreast of late-breaking developments and new advances in this rapidly developing field.

Author : Ian Goodfellow,Yoshua Bengio,Aaron Courville
Publisher : MIT Press
Page : 801 pages
File Size : 49,9 Mb
Release : 2016-11-10
Category : Computers
ISBN : 9780262337373

Get Book

Deep Learning by Ian Goodfellow,Yoshua Bengio,Aaron Courville Pdf

An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

Author : Pietro Michelucci
Publisher : Springer Science & Business Media
Page : 1051 pages
File Size : 45,6 Mb
Release : 2013-12-04
Category : Computers
ISBN : 9781461488064

Get Book

Handbook of Human Computation by Pietro Michelucci Pdf

This volume addresses the emerging area of human computation, The chapters, written by leading international researchers, explore existing and future opportunities to combine the respective strengths of both humans and machines in order to create powerful problem-solving capabilities. The book bridges scientific communities, capturing and integrating the unique perspective and achievements of each. It coalesces contributions from industry and across related disciplines in order to motivate, define, and anticipate the future of this exciting new frontier in science and cultural evolution. Readers can expect to find valuable contributions covering Foundations; Application Domains; Techniques and Modalities; Infrastructure and Architecture; Algorithms; Participation; Analysis; Policy and Security and the Impact of Human Computation. Researchers and professionals will find the Handbook of Human Computation a valuable reference tool. The breadth of content also provides a thorough foundation for students of the field.

Author : Romain Brette,Alain Destexhe
Publisher : Cambridge University Press
Page : 493 pages
File Size : 49,8 Mb
Release : 2012-09-06
Category : Mathematics
ISBN : 9780521516228

Get Book

Handbook of Neural Activity Measurement by Romain Brette,Alain Destexhe Pdf

Underlying principles of the various techniques are explained, enabling neuroscientists to extract meaningful information from their measurements.

Author : Duc T. Pham,Xing Liu
Publisher : Springer Science & Business Media
Page : 243 pages
File Size : 44,5 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9781447132448

Get Book

Neural Networks for Identification, Prediction and Control by Duc T. Pham,Xing Liu Pdf

In recent years, there has been a growing interest in applying neural networks to dynamic systems identification (modelling), prediction and control. Neural networks are computing systems characterised by the ability to learn from examples rather than having to be programmed in a conventional sense. Their use enables the behaviour of complex systems to be modelled and predicted and accurate control to be achieved through training, without a priori information about the systems' structures or parameters. This book describes examples of applications of neural networks In modelling, prediction and control. The topics covered include identification of general linear and non-linear processes, forecasting of river levels, stock market prices and currency exchange rates, and control of a time-delayed plant and a two-joint robot. These applications employ the major types of neural networks and learning algorithms. The neural network types considered in detail are the muhilayer perceptron (MLP), the Elman and Jordan networks and the Group-Method-of-Data-Handling (GMDH) network. In addition, cerebellar-model-articulation-controller (CMAC) networks and neuromorphic fuzzy logic systems are also presented. The main learning algorithm adopted in the applications is the standard backpropagation (BP) algorithm. Widrow-Hoff learning, dynamic BP and evolutionary learning are also described.

Author : Ivan Nunes da Silva,Danilo Hernane Spatti,Rogerio Andrade Flauzino,Luisa Helena Bartocci Liboni,Silas Franco dos Reis Alves
Publisher : Springer
Page : 307 pages
File Size : 44,8 Mb
Release : 2016-08-24
Category : Technology & Engineering
ISBN : 9783319431628

Get Book

Artificial Neural Networks by Ivan Nunes da Silva,Danilo Hernane Spatti,Rogerio Andrade Flauzino,Luisa Helena Bartocci Liboni,Silas Franco dos Reis Alves Pdf

This book provides comprehensive coverage of neural networks, their evolution, their structure, the problems they can solve, and their applications. The first half of the book looks at theoretical investigations on artificial neural networks and addresses the key architectures that are capable of implementation in various application scenarios. The second half is designed specifically for the production of solutions using artificial neural networks to solve practical problems arising from different areas of knowledge. It also describes the various implementation details that were taken into account to achieve the reported results. These aspects contribute to the maturation and improvement of experimental techniques to specify the neural network architecture that is most appropriate for a particular application scope. The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals.

Author : Panagiotis Vlamos,Ilias S. Kotsireas,Ioannis Tarnanas
Publisher : Springer Nature
Page : 1031 pages
File Size : 51,5 Mb
Release : 2023-07-25
Category : Medical
ISBN : 9783319759227

Get Book

Handbook of Computational Neurodegeneration by Panagiotis Vlamos,Ilias S. Kotsireas,Ioannis Tarnanas Pdf

The Handbook of Computational Neurodegeneration provides a comprehensive overview of the field and thus bridges the gap between standard textbooks of research on neurodegeneration and dispersed publications for specialists that have a narrowed focus on computational methods to study this complicated process. The handbook reviews the central issues and methodological approaches related to the field for which the reader pursues a thorough overview. It also conveys more advanced knowledge, thus serving both as an introductory text and as a starting point for an in-depth study of a specific area, as well as a quick reference source for the expert by reflecting the state of the art and future prospects. The book includes topics that are usually missing in standard textbooks and that are only marginally represented in the specific literature. The broad scope of this handbook is reflected by five major parts that facilitate an integration of computational concepts, methods and applications in the study of neurodegeneration. Each part is intended to stand on its own, giving an overview of the topic and the most important problems and approaches, which are supported by examples, practical applications, and proposed methodologies. The basic concepts and knowledge, standard procedures and methods are presented, as well as recent advances and new perspectives.

Author : Grzegorz Rozenberg,Thomas Bäck,Joost N. Kok
Publisher : Springer
Page : 2052 pages
File Size : 47,6 Mb
Release : 2012-07-09
Category : Computers
ISBN : 3540929096

Get Book

Handbook of Natural Computing by Grzegorz Rozenberg,Thomas Bäck,Joost N. Kok Pdf

Natural Computing is the field of research that investigates both human-designed computing inspired by nature and computing taking place in nature, i.e., it investigates models and computational techniques inspired by nature and also it investigates phenomena taking place in nature in terms of information processing. Examples of the first strand of research covered by the handbook include neural computation inspired by the functioning of the brain; evolutionary computation inspired by Darwinian evolution of species; cellular automata inspired by intercellular communication; swarm intelligence inspired by the behavior of groups of organisms; artificial immune systems inspired by the natural immune system; artificial life systems inspired by the properties of natural life in general; membrane computing inspired by the compartmentalized ways in which cells process information; and amorphous computing inspired by morphogenesis. Other examples of natural-computing paradigms are molecular computing and quantum computing, where the goal is to replace traditional electronic hardware, e.g., by bioware in molecular computing. In molecular computing, data are encoded as biomolecules and then molecular biology tools are used to transform the data, thus performing computations. In quantum computing, one exploits quantum-mechanical phenomena to perform computations and secure communications more efficiently than classical physics and, hence, traditional hardware allows. The second strand of research covered by the handbook, computation taking place in nature, is represented by investigations into, among others, the computational nature of self-assembly, which lies at the core of nanoscience, the computational nature of developmental processes, the computational nature of biochemical reactions, the computational nature of bacterial communication, the computational nature of brain processes, and the systems biology approach to bionetworks where cellular processes are treated in terms of communication and interaction, and, hence, in terms of computation. We are now witnessing exciting interaction between computer science and the natural sciences. While the natural sciences are rapidly absorbing notions, techniques and methodologies intrinsic to information processing, computer science is adapting and extending its traditional notion of computation, and computational techniques, to account for computation taking place in nature around us. Natural Computing is an important catalyst for this two-way interaction, and this handbook is a major record of this important development.

Author : Michael A. Arbib
Publisher : MIT Press (MA)
Page : 1118 pages
File Size : 43,7 Mb
Release : 1998
Category : Computers
ISBN : 0262511029

Get Book

The Handbook of Brain Theory and Neural Networks by Michael A. Arbib Pdf

Choice Outstanding Academic Title, 1996. In hundreds of articles by experts from around the world, and in overviews and "road maps" prepared by the editor, The Handbook of Brain Theory and Neural Networks charts the immense progress made in recent years in many specific areas related to great questions: How does the brain work? How can we build intelligent machines? While many books discuss limited aspects of one subfield or another of brain theory and neural networks, the Handbook covers the entire sweep of topics—from detailed models of single neurons, analyses of a wide variety of biological neural networks, and connectionist studies of psychology and language, to mathematical analyses of a variety of abstract neural networks, and technological applications of adaptive, artificial neural networks. Expository material makes the book accessible to readers with varied backgrounds while still offering a clear view of the recent, specialized research on specific topics.