Handbook of Neural Computation

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  • Author : Pijush Samui
  • Publisher : Academic Press
  • Pages : 600 pages
  • ISBN : 9780128113189
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Handbook of Neural Computation

Download or Read online Handbook of Neural Computation full in PDF, ePub and kindle. this book written by Pijush Samui and published by Academic Press which was released on 28 July 2017 with total page 600 pages. We cannot guarantee that Handbook of Neural Computation book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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

Handbook of Neural Computation

Handbook of Neural Computation
  • Author : Pijush Samui,Sanjiban Sekhar Roy,Valentina E. Balas
  • Publisher : Academic Press
  • Release : 28 July 2017
GET THIS BOOK Handbook of Neural Computation

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

Handbook of Neural Computation

Handbook of Neural Computation
  • Author : Emile Fiesler,Russell Beale
  • Publisher : CRC Press
  • Release : 15 January 2020
GET THIS BOOK Handbook of Neural Computation

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 probl

Handbook of Neural Computation

Handbook of Neural Computation
  • Author : Pijush Samui,Sanjiban Sekhar Roy,Valentina E. Balas
  • Publisher : Academic Press
  • Release : 18 July 2017
GET THIS BOOK Handbook of Neural Computation

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

Handbook of Neural Computing Applications

Handbook of Neural Computing Applications
  • Author : Alianna J. Maren,Craig T. Harston,Robert M. Pap
  • Publisher : Academic Press
  • Release : 10 May 2014
GET THIS BOOK Handbook of Neural Computing Applications

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

Handbook of Neural Computation

Handbook of Neural Computation
  • Author : Emile Fiesler,Russell Beale
  • Publisher : CRC Press
  • Release : 01 January 1997
GET THIS BOOK Handbook of Neural Computation

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.

Handbook on Neural Information Processing

Handbook on Neural Information Processing
  • Author : Monica Bianchini,Marco Maggini,Lakhmi C. Jain
  • Publisher : Springer Science & Business Media
  • Release : 12 April 2013
GET THIS BOOK Handbook on Neural Information Processing

This handbook presents some of the most recent topics in neural information processing, covering both theoretical concepts and practical applications. The contributions include: Deep architectures Recurrent, recursive, and graph neural networks Cellular neural networks Bayesian networks Approximation capabilities of neural networks Semi-supervised learning Statistical relational learning Kernel methods for structured data Multiple classifier systems Self organisation and modal learning Applications to content-based image retrieval, text mining in large document collections, and bioinformatics This book is thought particularly for graduate students,

Handbook of Neural Network Signal Processing

Handbook of Neural Network Signal Processing
  • Author : Yu Hen Hu,Jenq-Neng Hwang
  • Publisher : CRC Press
  • Release : 03 October 2018
GET THIS BOOK Handbook of Neural Network Signal Processing

The use of neural networks is permeating every area of signal processing. They can provide powerful means for solving many problems, especially in nonlinear, real-time, adaptive, and blind signal processing. The Handbook of Neural Network Signal Processing brings together applications that were previously scattered among various publications to provide an up-to-date, detailed treatment of the subject from an engineering point of view. The authors cover basic principles, modeling, algorithms, architectures, implementation procedures, and well-designed simulation examples of audio, video, speech,

The Handbook of Brain Theory and Neural Networks

The Handbook of Brain Theory and Neural Networks
  • Author : Michael A. Arbib,Fletcher Jones Professor of Computer Science and Professor of Biological Sciences Biomedical Engineering Neuroscience and Psychology Michael A Arbib,Prudence H. Arbib
  • Publisher : MIT Press
  • Release : 04 July 2022
GET THIS BOOK The Handbook of Brain Theory and Neural Networks

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).

Computer Modelling of Social Processes

Computer Modelling of Social Processes
  • Author : Wim B. G. Liebrand Andrzej Nowak Rainer Hegselmann
  • Publisher : SAGE
  • Release : 08 June 1998
GET THIS BOOK Computer Modelling of Social Processes

This book introduces and the new computer-based research methods for studying and modeling complex social phenomena. It is the first coherent collection that surveys the impact that computer-based methods have had on the social and behavioural sciences and illustrates the potential for future research. The methods are presented in an accessible manner and do not assume any background in computer science. The authors introduce each chapter and explain how computers can help to study social processes and each method is

Neural Networks and Soft Computing

Neural Networks and Soft Computing
  • Author : Leszek Rutkowski
  • Publisher : Springer Science & Business Media
  • Release : 20 March 2013
GET THIS BOOK Neural Networks and Soft Computing

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

Advances in Neural Computation Machine Learning and Cognitive Research II

Advances in Neural Computation  Machine Learning  and Cognitive Research II
  • Author : Boris Kryzhanovsky,Witali Dunin-Barkowski,Vladimir Redko,Yury Tiumentsev
  • Publisher : Springer
  • Release : 06 October 2018
GET THIS BOOK Advances in Neural Computation Machine Learning and Cognitive Research II

This book describes new theories and applications of artificial neural networks, with a special focus on addressing problems in neuroscience, biology and biophysics and cognitive research. It covers a wide range of methods and technologies, including deep neural networks, large-scale neural models, brain–computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more. The book includes both selected and invited papers presented at the XX International Conference on Neuroinformatics, held in

Handbook of Neural Network Signal Processing

Handbook of Neural Network Signal Processing
  • Author : Yu Hen Hu,Jenq-Neng Hwang
  • Publisher : CRC Press
  • Release : 03 October 2018
GET THIS BOOK Handbook of Neural Network Signal Processing

The use of neural networks is permeating every area of signal processing. They can provide powerful means for solving many problems, especially in nonlinear, real-time, adaptive, and blind signal processing. The Handbook of Neural Network Signal Processing brings together applications that were previously scattered among various publications to provide an up-to-date, detailed treatment of the subject from an engineering point of view. The authors cover basic principles, modeling, algorithms, architectures, implementation procedures, and well-designed simulation examples of audio, video, speech,

New Trends in Neural Computation

New Trends in Neural Computation
  • Author : International Workshop on Artificial Neural Networks$ (1993 : Sitges, Espagne),Jose Mira,Joan Cabestany,Alberto Prieto
  • Publisher : Springer Science & Business Media
  • Release : 27 May 1993
GET THIS BOOK New Trends in Neural Computation

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