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Science Of Artificial Neural Networks


Science Of Artificial Neural Networks
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Principles Of Artificial Neural Networks


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.


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.



Interdisciplinary Computing In Java Programming


Interdisciplinary Computing In Java Programming
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Author : Sun-Chong Wang
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Interdisciplinary Computing In Java Programming written by Sun-Chong Wang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.


Books on computation in the marketplace tend to discuss the topics within specific fields. Many computational algorithms, however, share common roots. Great advantages emerge if numerical methodologies break the boundaries and find their uses across disciplines. Interdisciplinary Computing In Java Programming Language introduces readers of different backgrounds to the beauty of the selected algorithms. Serious quantitative researchers, writing customized codes for computation, enjoy cracking source codes as opposed to the black-box approach. Most C and Fortran programs, despite being slightly faster in program execution, lack built-in support for plotting and graphical user interface. This book selects Java as the platform where source codes are developed and applications are run, helping readers/users best appreciate the fun of computation. Interdisciplinary Computing In Java Programming Language is designed to meet the needs of a professional audience composed of practitioners and researchers in science and technology. This book is also suitable for senior undergraduate and graduate-level students in computer science, as a secondary text.



Artificial Neural Networks


Artificial Neural Networks
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Author : David J. Livingstone
language : en
Publisher: Humana Press
Release Date : 2011-10-09

Artificial Neural Networks written by David J. Livingstone and has been published by Humana Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-09 with Computers categories.


In this book, international experts report the history of the application of ANN to chemical and biological problems, provide a guide to network architectures, training and the extraction of rules from trained networks, and cover many cutting-edge examples of the application of ANN to chemistry and biology. Methods involving the mapping and interpretation of Infra Red spectra and modelling environmental toxicology are included. This book is an excellent guide to this exciting field.



Elements Of Artificial Neural Networks


Elements Of Artificial Neural Networks
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Author : Kishan Mehrotra
language : en
Publisher: MIT Press
Release Date : 1997

Elements Of Artificial Neural Networks written by Kishan Mehrotra and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Computers categories.


Elements of Artificial Neural Networks provides a clearly organized general introduction, focusing on a broad range of algorithms, for students and others who want to use neural networks rather than simply study them. The authors, who have been developing and team teaching the material in a one-semester course over the past six years, describe most of the basic neural network models (with several detailed solved examples) and discuss the rationale and advantages of the models, as well as their limitations. The approach is practical and open-minded and requires very little mathematical or technical background. Written from a computer science and statistics point of view, the text stresses links to contiguous fields and can easily serve as a first course for students in economics and management. The opening chapter sets the stage, presenting the basic concepts in a clear and objective way and tackling important -- yet rarely addressed -- questions related to the use of neural networks in practical situations. Subsequent chapters on supervised learning (single layer and multilayer networks), unsupervised learning, and associative models are structured around classes of problems to which networks can be applied. Applications are discussed along with the algorithms. A separate chapter takes up optimization methods. The most frequently used algorithms, such as backpropagation, are introduced early on, right after perceptrons, so that these can form the basis for initiating course projects. Algorithms published as late as 1995 are also included. All of the algorithms are presented using block-structured pseudo-code, and exercises are provided throughout. Software implementing many commonly used neural network algorithms is available at the book's website. Transparency masters, including abbreviated text and figures for the entire book, are available for instructors using the text.



Artificial Neural Networks


Artificial Neural Networks
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Author : P.J. Braspenning
language : en
Publisher: Springer Science & Business Media
Release Date : 1995-06-02

Artificial Neural Networks written by P.J. Braspenning and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-06-02 with Computers categories.


This book presents carefully revised versions of tutorial lectures given during a School on Artificial Neural Networks for the industrial world held at the University of Limburg in Maastricht, Belgium. The major ANN architectures are discussed to show their powerful possibilities for empirical data analysis, particularly in situations where other methods seem to fail. Theoretical insight is offered by examining the underlying mathematical principles in a detailed, yet clear and illuminating way. Practical experience is provided by discussing several real-world applications in such areas as control, optimization, pattern recognition, software engineering, robotics, operations research, and CAM.



Artificial Neural Networks In Hydrology


Artificial Neural Networks In Hydrology
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Author : R.S. Govindaraju
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09

Artificial Neural Networks In Hydrology written by R.S. Govindaraju and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Science categories.


R. S. GOVINDARAJU and ARAMACHANDRA RAO School of Civil Engineering Purdue University West Lafayette, IN. , USA Background and Motivation The basic notion of artificial neural networks (ANNs), as we understand them today, was perhaps first formalized by McCulloch and Pitts (1943) in their model of an artificial neuron. Research in this field remained somewhat dormant in the early years, perhaps because of the limited capabilities of this method and because there was no clear indication of its potential uses. However, interest in this area picked up momentum in a dramatic fashion with the works of Hopfield (1982) and Rumelhart et al. (1986). Not only did these studies place artificial neural networks on a firmer mathematical footing, but also opened the dOOf to a host of potential applications for this computational tool. Consequently, neural network computing has progressed rapidly along all fronts: theoretical development of different learning algorithms, computing capabilities, and applications to diverse areas from neurophysiology to the stock market. . Initial studies on artificial neural networks were prompted by adesire to have computers mimic human learning. As a result, the jargon associated with the technical literature on this subject is replete with expressions such as excitation and inhibition of neurons, strength of synaptic connections, learning rates, training, and network experience. ANNs have also been referred to as neurocomputers by people who want to preserve this analogy.



Artificial Higher Order Neural Networks For Modeling And Simulation


Artificial Higher Order Neural Networks For Modeling And Simulation
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Author : Zhang, Ming
language : en
Publisher: IGI Global
Release Date : 2012-10-31

Artificial Higher Order Neural Networks For Modeling And Simulation written by Zhang, Ming and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-31 with Computers categories.


"This book introduces Higher Order Neural Networks (HONNs) to computer scientists and computer engineers as an open box neural networks tool when compared to traditional artificial neural networks"--Provided by publisher.



Multivariate Statistical Machine Learning Methods For Genomic Prediction


Multivariate Statistical Machine Learning Methods For Genomic Prediction
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Author : Osval Antonio Montesinos López
language : en
Publisher: Springer Nature
Release Date : 2022-02-14

Multivariate Statistical Machine Learning Methods For Genomic Prediction written by Osval Antonio Montesinos López and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-14 with Technology & Engineering categories.


This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.



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


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.



Focus On Artificial Neural Networks


Focus On Artificial Neural Networks
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Author : John A. Flores
language : en
Publisher:
Release Date : 2011-01-01

Focus On Artificial Neural Networks written by John A. Flores and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-01 with Artificial intelligence categories.


This book gathers the most current research from across the globe in the study of artificial neural networks. Topics discussed include artificial neural networks in environmental sciences and chemical engineering; application of artificial neural networks in the development of pharamceutical microemulsions; massive-training artificial neural networks for supervised enhancement/suppression of lesions/patterns in medical images; evidences of new biophysical properties of microtubules; neural network applications in modern induction machine control systems and wavelet neural networks.