An Introduction To Neural Computing

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An Introduction to Neural Computing

Author : Igor Aleksander,Helen Morton
Publisher : Van Nostrand Reinhold Company
Page : 276 pages
File Size : 52,5 Mb
Release : 1990
Category : Computers
ISBN : UOM:39015019643264

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An Introduction to Neural Computing by Igor Aleksander,Helen Morton Pdf

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.

An Introduction to Neural Networks

Author : James A. Anderson
Publisher : MIT Press
Page : 680 pages
File Size : 41,8 Mb
Release : 1995
Category : Computers
ISBN : 0262510812

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An Introduction to Neural Networks by James A. Anderson Pdf

An Introduction to Neural Networks falls into a new ecological niche for texts. Based on notes that have been class-tested for more than a decade, it is aimed at cognitive science and neuroscience students who need to understand brain function in terms of computational modeling, and at engineers who want to go beyond formal algorithms to applications and computing strategies. It is the only current text to approach networks from a broad neuroscience and cognitive science perspective, with an emphasis on the biology and psychology behind the assumptions of the models, as well as on what the models might be used for. It describes the mathematical and computational tools needed and provides an account of the author's own ideas. Students learn how to teach arithmetic to a neural network and get a short course on linear associative memory and adaptive maps. They are introduced to the author's brain-state-in-a-box (BSB) model and are provided with some of the neurobiological background necessary for a firm grasp of the general subject. The field now known as neural networks has split in recent years into two major groups, mirrored in the texts that are currently available: the engineers who are primarily interested in practical applications of the new adaptive, parallel computing technology, and the cognitive scientists and neuroscientists who are interested in scientific applications. As the gap between these two groups widens, Anderson notes that the academics have tended to drift off into irrelevant, often excessively abstract research while the engineers have lost contact with the source of ideas in the field. Neuroscience, he points out, provides a rich and valuable source of ideas about data representation and setting up the data representation is the major part of neural network programming. Both cognitive science and neuroscience give insights into how this can be done effectively: cognitive science suggests what to compute and neuroscience suggests how to compute it.

Neural Computing - An Introduction

Author : R Beale,T Jackson
Publisher : CRC Press
Page : 260 pages
File Size : 41,5 Mb
Release : 1990-01-01
Category : Mathematics
ISBN : 1420050435

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Neural Computing - An Introduction by R Beale,T Jackson Pdf

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.

Introduction To The Theory Of Neural Computation

Author : John A. Hertz
Publisher : CRC Press
Page : 352 pages
File Size : 55,7 Mb
Release : 2018-03-08
Category : Science
ISBN : 9780429968211

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Introduction To The Theory Of Neural Computation by John A. Hertz Pdf

Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest.

An Introduction to Neural Computing

Author : Igor Aleksander,Helen Morton
Publisher : Unknown
Page : 322 pages
File Size : 53,5 Mb
Release : 1995
Category : Computers
ISBN : UOM:39015034899974

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An Introduction to Neural Computing by Igor Aleksander,Helen Morton Pdf

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.

An Introduction to Neural Networks

Author : Kevin Gurney
Publisher : CRC Press
Page : 234 pages
File Size : 54,6 Mb
Release : 2018-10-08
Category : Computers
ISBN : 9781482286991

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An Introduction to Neural Networks by Kevin Gurney Pdf

Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back-propagation; associative memory and Hopfield nets; and self-organization and feature maps. The traditionally difficult topic of adaptive resonance theory is clarified within a hierarchical description of its operation. The book also includes several real-world examples to provide a concrete focus. This should enhance its appeal to those involved in the design, construction and management of networks in commercial environments and who wish to improve their understanding of network simulator packages. As a comprehensive and highly accessible introduction to one of the most important topics in cognitive and computer science, this volume should interest a wide range of readers, both students and professionals, in cognitive science, psychology, computer science and electrical engineering.

Neural Networks

Author : Raul Rojas
Publisher : Springer Science & Business Media
Page : 511 pages
File Size : 42,6 Mb
Release : 2013-06-29
Category : Computers
ISBN : 9783642610684

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Neural Networks by Raul Rojas Pdf

Neural networks are a computing paradigm that is finding increasing attention among computer scientists. In this book, theoretical laws and models previously scattered in the literature are brought together into a general theory of artificial neural nets. Always with a view to biology and starting with the simplest nets, it is shown how the properties of models change when more general computing elements and net topologies are introduced. Each chapter contains examples, numerous illustrations, and a bibliography. The book is aimed at readers who seek an overview of the field or who wish to deepen their knowledge. It is suitable as a basis for university courses in neurocomputing.

An Information-Theoretic Approach to Neural Computing

Author : Gustavo Deco,Dragan Obradovic
Publisher : Springer Science & Business Media
Page : 265 pages
File Size : 42,6 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781461240167

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An Information-Theoretic Approach to Neural Computing by Gustavo Deco,Dragan Obradovic Pdf

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.

Rough-Neural Computing

Author : Sankar Kumar Pal,Lech Polkowski
Publisher : Springer Science & Business Media
Page : 741 pages
File Size : 46,9 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9783642188596

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Rough-Neural Computing by Sankar Kumar Pal,Lech Polkowski Pdf

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.

Handbook of Neural Computing Applications

Author : Alianna J. Maren,Craig T. Harston,Robert M. Pap
Publisher : Academic Press
Page : 470 pages
File Size : 46,9 Mb
Release : 2014-05-10
Category : Computers
ISBN : 9781483264844

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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.

Advanced Methods in Neural Computing

Author : Philip D. Wasserman
Publisher : Van Nostrand Reinhold Company
Page : 280 pages
File Size : 46,8 Mb
Release : 1993
Category : Computers
ISBN : UOM:39015029904201

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Advanced Methods in Neural Computing by Philip D. Wasserman Pdf

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.

Guide to Neural Computing Applications

Author : Lionel Tarassenko
Publisher : Elsevier
Page : 160 pages
File Size : 49,6 Mb
Release : 1998-01-30
Category : Computers
ISBN : 9780080512600

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Guide to Neural Computing Applications by Lionel Tarassenko Pdf

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.

Introduction to Neural Networks with Java

Author : Jeff Heaton
Publisher : Heaton Research Incorporated
Page : 380 pages
File Size : 42,8 Mb
Release : 2005
Category : Computers
ISBN : 9780977320608

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Introduction to Neural Networks with Java by Jeff Heaton Pdf

In addition to showing the programmer how to construct Neural Networks, the book discusses the Java Object Oriented Neural Engine (JOONE), a free open source Java neural engine. (Computers)

Neural Networks and Deep Learning

Author : Charu C. Aggarwal
Publisher : Springer
Page : 497 pages
File Size : 53,9 Mb
Release : 2018-08-25
Category : Computers
ISBN : 9783319944630

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Neural Networks and Deep Learning by Charu C. Aggarwal Pdf

This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Applications associated with many different areas like recommender systems, machine translation, image captioning, image classification, reinforcement-learning based gaming, and text analytics are covered. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. These methods are studied together with recent feature engineering methods like word2vec. Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 3 and 4. Chapters 5 and 6 present radial-basis function (RBF) networks and restricted Boltzmann machines. Advanced topics in neural networks: Chapters 7 and 8 discuss recurrent neural networks and convolutional neural networks. Several advanced topics like deep reinforcement learning, neural Turing machines, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 9 and 10. The book is written for graduate students, researchers, and practitioners. Numerous exercises are available along with a solution manual to aid in classroom teaching. Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.

Intro to Neutral Computing

Author : Igor Aleksander
Publisher : Van Nostrand Reinhold Company
Page : 240 pages
File Size : 50,6 Mb
Release : 1990-07-01
Category : Electronic
ISBN : 0442312180

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Intro to Neutral Computing by Igor Aleksander Pdf