Handbook of Neural Computation

• Author : Pijush Samui,Sanjiban Sekhar Roy,Valentina E. Balas
• Publisher : Academic Press
• Release : 28 July 2017

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

• Author : Emile Fiesler,Russell Beale
• Publisher : CRC Press
• Release : 15 January 2020

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

• Author : Pijush Samui,Sanjiban Sekhar Roy,Valentina E. Balas
• Publisher : Academic Press
• Release : 18 July 2017

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

• Author : Alianna J. Maren,Craig T. Harston,Robert M. Pap
• Publisher : Academic Press
• Release : 10 May 2014

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

• Author : Emile Fiesler,Russell Beale
• Publisher : CRC Press
• Release : 01 January 1997

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.

• Author : Monica Bianchini,Marco Maggini,Lakhmi C. Jain
• Publisher : Springer Science & Business Media
• Release : 12 April 2013

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,

• Author : Yu Hen Hu,Jenq-Neng Hwang
• Publisher : CRC Press
• Release : 03 October 2018

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,

• 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

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 : Wim B. G. Liebrand Andrzej Nowak Rainer Hegselmann
• Publisher : SAGE
• Release : 08 June 1998

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

• Author : Beale Fiesler
• Publisher : Unknown
• Release : 04 July 2022

• Author : Leszek Rutkowski
• Publisher : Springer Science & Business Media
• Release : 20 March 2013

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

• Author : Boris Kryzhanovsky,Witali Dunin-Barkowski,Vladimir Redko,Yury Tiumentsev
• Publisher : Springer
• Release : 06 October 2018

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

• Author : Anonim
• Publisher : IOS Press
• Release : 04 July 2022

• Author : Yu Hen Hu,Jenq-Neng Hwang
• Publisher : CRC Press
• Release : 03 October 2018

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,

• 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

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