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Principles Of Artificial Neural Networks

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Principles Of Artificial Neural Networks Basic Designs To Deep Learning 4th Edition

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Author : Daniel Graupe
language : en
Publisher: World Scientific
Release Date : 2019-03-15

Principles Of Artificial Neural Networks Basic Designs To Deep Learning 4th Edition written by Daniel Graupe and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-15 with Computers categories.

The field of Artificial Neural Networks is the fastest growing field in Information Technology and specifically, in Artificial Intelligence and Machine Learning.This must-have compendium presents the theory and case studies of artificial neural networks. The volume, with 4 new chapters, updates the earlier edition by highlighting recent developments in Deep-Learning Neural Networks, which are the recent leading approaches to neural networks. Uniquely, the book also includes case studies of applications of neural networks — demonstrating how such case studies are designed, executed and how their results are obtained.The title is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining.

Principles Of Artificial Neural Networks 3rd Edition

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Author : Daniel Graupe
language : en
Publisher: World Scientific
Release Date : 2013-07-31

Principles Of Artificial Neural Networks 3rd Edition written by Daniel Graupe and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-31 with Computers categories.

Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in medicine, in finance, in security and beyond.This volume covers the basic theory and architecture of the major artificial neural networks. Uniquely, it presents 18 complete case studies of applications of neural networks in various fields, ranging from cell-shape classification to micro-trading in finance and to constellation recognition — all with their respective source codes. These case studies demonstrate to the readers in detail how such case studies are designed and executed and how their specific results are obtained.The book is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers in medicine, finance and data mining.

Principles Of Artificial Neural Networks

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Author : Daniel Graupe
language : en
Publisher: World Scientific
Release Date : 2007

Principles Of Artificial Neural Networks written by Daniel Graupe and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.

The book should serve as a text for a university graduate course or for an advanced undergraduate course on neural networks in engineering and computer science departments. It should also serve as a self-study course for engineers and computer scientists in the industry. Covering major neural network approaches and architectures with the theories, this text presents detailed case studies for each of the approaches, accompanied with complete computer codes and the corresponding computed results. The case studies are designed to allow easy comparison of network performance to illustrate strengths and weaknesses of the different networks.

Principles Of Artificial Neural Networks

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Author : Wai-kai Chen
language : en
Publisher: World Scientific Publishing Company
Release Date : 1997-07-15

Principles Of Artificial Neural Networks written by Wai-kai Chen and has been published by World Scientific Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-07-15 with Technology & Engineering categories.

This textbook is intended for a first-year graduate course on Artificial Neural Networks. It assumes no prior background in the subject and is directed to MS students in electrical engineering, computer science and related fields, with background in at least one programming language or in a programming tool such as Matlab, and who have taken the basic undergraduate classes in systems or in signal processing.The uniqueness of the book is in the breadth of its coverage over the range of all major artificial neural network approaches and in extensive hands-on case-studies on each and every neural network considered. These detailed case studies include complete program print-outs and results and deal with a range of problems, to illustrate the reader's ability to solve problems ranging from speech recognition, character recognition to control and signal processing problems, all on the basis of following the present text. Another unique aspect of the text is its coverage of important new topics of recurrent (time-cycling) networks and of large memory storage and retrieval problems.The text also attempts to show the reader how he can modify or combine one or more of the neural networks covered, to tailor them to a given problem which does not appear to fit any of the more standard designs, as is very often the case.

Principles Of Artificial Neural Networks

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Author : Daniel Graupe
language : en
Publisher:
Release Date : 2019

Principles Of Artificial Neural Networks written by Daniel Graupe and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with COMPUTERS categories.

Neural Network Principles

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Author : Robert L. Harvey
language : en
Publisher:
Release Date : 1994

Neural Network Principles written by Robert L. Harvey and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with Computers categories.

Using models of biological systems as springboards to a broad range of applications, this volume presents the basic ideas of neural networks in mathematical form. Comprehensive in scope, Neural Network Principles outlines the structure of the human brain, explains the physics of neurons, derives the standard neuron state equations, and presents the consequences of these mathematical models. Author Robert L. Harvey derives a set of simple networks that can filter, recall, switch, amplify, and recognize input signals that are all patterns of neuron activation. The author also discusses properties of general interconnected neuron groups, including the well-known Hopfield and perception neural networks using a unified approach along with suggestions of new design procedures for both. He then applies the theory to synthesize artificial neural networks for specialized tasks. In addition, Neural Network Principles outlines the design of machine vision systems, explores motor control of the human brain and presents two examples of artificial hand-eye systems, demonstrates how to solve large systems of interconnected neurons, and considers control and modulation in the human brain-mind with insights for a new understanding of many mental illnesses.

Principles Of Artificial Neural Networks

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Author : Daniel Graupe
language : en
Publisher: World Scientific
Release Date : 1997-05-01

Principles Of Artificial Neural Networks

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Author : Daniel Graupe
language : en
Publisher: World Scientific
Release Date : 2007

This book should serves as a self-study course for engineers and computer scientist in the industry. The features include major neural network approaches and architectures with theories and detailed case studies for each of the approaches acompanied by complete computer codes and the corresponding computed results. There is also a chapter on LAMSTAR neural network.

Designs And Applied Principles Of Artificial Neural Networks

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Author : Jeremy Rogerson
language : en
Publisher:
Release Date : 2015-03-23

Designs And Applied Principles Of Artificial Neural Networks written by Jeremy Rogerson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-23 with Neural networks (Computer science) categories.

This book presents a broad overview on the current various design modules and applications of artificial neural systems. Artificial neural networks are often dubbed as one of the most acknowledged technologies in the past twenty years. It has been broadly applied in a wide diversity of applications. The aim of this book is to present current developments of architectures, methodologies, and usage of artificial neural networks. The topics in this book majorly deal with two important aspects: the architecture aspect involving dealing with architectures, design, optimization, and the analysis of artificial neural networks; and the application aspect dealing with applications of artificial neural networks in a broad spectrum of areas comprising of biomedical, industrial, physics, and financial applications. This book will be an important source of reference for graduate students and engineers in various organizations.

Artificial Neural Networks

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Author : B. YEGNANARAYANA
language : en
Publisher: PHI Learning Pvt. Ltd.
Release Date : 2009-01-14

Artificial Neural Networks written by B. YEGNANARAYANA and has been published by PHI Learning Pvt. Ltd. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-14 with Computers categories.

Designed as an introductory level textbook on Artificial Neural Networks at the postgraduate and senior undergraduate levels in any branch of engineering, this self-contained and well-organized book highlights the need for new models of computing based on the fundamental principles of neural networks. Professor Yegnanarayana compresses, into the covers of a single volume, his several years of rich experience, in teaching and research in the areas of speech processing, image processing, artificial intelligence and neural networks. He gives a masterly analysis of such topics as Basics of artificial neural networks, Functional units of artificial neural networks for pattern recognition tasks, Feedforward and Feedback neural networks, and Archi-tectures for complex pattern recognition tasks. Throughout, the emphasis is on the pattern processing feature of the neural networks. Besides, the presentation of real-world applications provides a practical thrust to the discussion.

Principles Of Artificial Neural Networks

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