Artificial Neural Systems

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Elements of Artificial Neural Networks

Author : Kishan Mehrotra
Publisher : MIT Press
ISBN 13 : 9780262133289
Total Pages : 376 pages
Book Rating : 4.1/5 (332 download)

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Book Synopsis Elements of Artificial Neural Networks by : Kishan Mehrotra

Download or read book Elements of Artificial Neural Networks written by Kishan Mehrotra and published by MIT Press. This book was released on 1997 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : P.J. Braspenning
Publisher : Springer Science & Business Media
ISBN 13 : 9783540594888
Total Pages : 320 pages
Book Rating : 4.5/5 (948 download)

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Book Synopsis Artificial Neural Networks by : P.J. Braspenning

Download or read book Artificial Neural Networks written by P.J. Braspenning and published by Springer Science & Business Media. This book was released on 1995-06-02 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Biomedicine

Author : Paulo J.G. Lisboa
Publisher : Springer Science & Business Media
ISBN 13 : 9781852330057
Total Pages : 314 pages
Book Rating : 4.3/5 (3 download)

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Book Synopsis Artificial Neural Networks in Biomedicine by : Paulo J.G. Lisboa

Download or read book Artificial Neural Networks in Biomedicine written by Paulo J.G. Lisboa and published by Springer Science & Business Media. This book was released on 2000-02-02 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides a state-of-the-art survey of artificial neural network applications in biomedical diagnosis, laboratory data analysis and related practical areas. It looks at biomedical applications which involve customising neural network technology to resolve specific difficulties with data processing, and deals with applications relating to particular aspects of clinical practice and laboratory or medically-related analysis. Each chapter is self-contained with regard to the technology used, covering important technical points and implementation issues like the design of user interfaces and hardware/software platforms. Artificial Neural Networks in Biomedicine will be of interest to computer scientists and neural network practitioners who want to extend their knowledge of issues relevant to biomedical applications, developers of clinical computer systems, and medical researchers looking for new methods and computational tools.

Artificial Neural Network Modelling

Author : Subana Shanmuganathan
Publisher : Springer
ISBN 13 : 3319284959
Total Pages : 468 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Artificial Neural Network Modelling by : Subana Shanmuganathan

Download or read book Artificial Neural Network Modelling written by Subana Shanmuganathan and published by Springer. This book was released on 2016-02-03 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling.

Artificial Neural Networks

Author : Ivan Nunes da Silva
Publisher : Springer
ISBN 13 : 3319431625
Total Pages : 309 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Artificial Neural Networks by : Ivan Nunes da Silva

Download or read book Artificial Neural Networks written by Ivan Nunes da Silva and published by Springer. This book was released on 2016-08-24 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides comprehensive coverage of neural networks, their evolution, their structure, the problems they can solve, and their applications. The first half of the book looks at theoretical investigations on artificial neural networks and addresses the key architectures that are capable of implementation in various application scenarios. The second half is designed specifically for the production of solutions using artificial neural networks to solve practical problems arising from different areas of knowledge. It also describes the various implementation details that were taken into account to achieve the reported results. These aspects contribute to the maturation and improvement of experimental techniques to specify the neural network architecture that is most appropriate for a particular application scope. The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals.

Fundamentals of Artificial Neural Networks

Author : Mohamad H. Hassoun
Publisher : MIT Press
ISBN 13 : 9780262082396
Total Pages : 546 pages
Book Rating : 4.0/5 (823 download)

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Book Synopsis Fundamentals of Artificial Neural Networks by : Mohamad H. Hassoun

Download or read book Fundamentals of Artificial Neural Networks written by Mohamad H. Hassoun and published by MIT Press. This book was released on 1995 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: A systematic account of artificial neural network paradigms that identifies fundamental concepts and major methodologies. Important results are integrated into the text in order to explain a wide range of existing empirical observations and commonly used heuristics.

Artificial Neural Networks

Author : Kevin L. Priddy
Publisher : SPIE Press
ISBN 13 : 9780819459879
Total Pages : 184 pages
Book Rating : 4.4/5 (598 download)

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Book Synopsis Artificial Neural Networks by : Kevin L. Priddy

Download or read book Artificial Neural Networks written by Kevin L. Priddy and published by SPIE Press. This book was released on 2005 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This tutorial text provides the reader with an understanding of artificial neural networks (ANNs), and their application, beginning with the biological systems which inspired them, through the learning methods that have been developed, and the data collection processes, to the many ways ANNs are being used today. The material is presented with a minimum of math (although the mathematical details are included in the appendices for interested readers), and with a maximum of hands-on experience. All specialized terms are included in a glossary. The result is a highly readable text that will teach the engineer the guiding principles necessary to use and apply artificial neural networks.

Neural Smithing

Author : Russell Reed
Publisher : MIT Press
ISBN 13 : 0262181908
Total Pages : 359 pages
Book Rating : 4.2/5 (621 download)

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Book Synopsis Neural Smithing by : Russell Reed

Download or read book Neural Smithing written by Russell Reed and published by MIT Press. This book was released on 1999-02-17 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks are nonlinear mapping systems whose structure is loosely based on principles observed in the nervous systems of humans and animals. The basic idea is that massive systems of simple units linked together in appropriate ways can generate many complex and interesting behaviors. This book focuses on the subset of feedforward artificial neural networks called multilayer perceptrons (MLP). These are the mostly widely used neural networks, with applications as diverse as finance (forecasting), manufacturing (process control), and science (speech and image recognition). This book presents an extensive and practical overview of almost every aspect of MLP methodology, progressing from an initial discussion of what MLPs are and how they might be used to an in-depth examination of technical factors affecting performance. The book can be used as a tool kit by readers interested in applying networks to specific problems, yet it also presents theory and references outlining the last ten years of MLP research.

Neural Systems for Control

Author : Omid Omidvar
Publisher : Elsevier
ISBN 13 : 0080537391
Total Pages : 375 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Neural Systems for Control by : Omid Omidvar

Download or read book Neural Systems for Control written by Omid Omidvar and published by Elsevier. This book was released on 1997-02-24 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Control problems offer an industrially important application and a guide to understanding control systems for those working in Neural Networks. Neural Systems for Control represents the most up-to-date developments in the rapidly growing aplication area of neural networks and focuses on research in natural and artifical neural systems directly applicable to control or making use of modern control theory. The book covers such important new developments in control systems such as intelligent sensors in semiconductor wafer manufacturing; the relation between muscles and cerebral neurons in speech recognition; online compensation of reconfigurable control for spacecraft aircraft and other systems; applications to rolling mills, robotics and process control; the usage of past output data to identify nonlinear systems by neural networks; neural approximate optimal control; model-free nonlinear control; and neural control based on a regulation of physiological investigation/blood pressure control. All researchers and students dealing with control systems will find the fascinating Neural Systems for Control of immense interest and assistance. - Focuses on research in natural and artifical neural systems directly applicable to contol or making use of modern control theory - Represents the most up-to-date developments in this rapidly growing application area of neural networks - Takes a new and novel approach to system identification and synthesis

Introduction to Artificial Neural Systems

Author : Jacek M. Zurada
Publisher : West Publishing Company
ISBN 13 :
Total Pages : 812 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Introduction to Artificial Neural Systems by : Jacek M. Zurada

Download or read book Introduction to Artificial Neural Systems written by Jacek M. Zurada and published by West Publishing Company. This book was released on 1992 with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Applications of Artificial Neural Networks for Nonlinear Data

Author : Patel, Hiral Ashil
Publisher : IGI Global
ISBN 13 : 1799840433
Total Pages : 315 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Applications of Artificial Neural Networks for Nonlinear Data by : Patel, Hiral Ashil

Download or read book Applications of Artificial Neural Networks for Nonlinear Data written by Patel, Hiral Ashil and published by IGI Global. This book was released on 2020-09-25 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Processing information and analyzing data efficiently and effectively is crucial for any company that wishes to stay competitive in its respective market. Nonlinear data presents new challenges to organizations, however, due to its complexity and unpredictability. The only technology that can properly handle this form of data is artificial neural networks. These modeling systems present a high level of benefits in analyzing complex data in a proficient manner, yet considerable research on the specific applications of these intelligent components is significantly deficient. Applications of Artificial Neural Networks for Nonlinear Data is a collection of innovative research on the contemporary nature of artificial neural networks and their specific implementations within data analysis. While highlighting topics including propagation functions, optimization techniques, and learning methodologies, this book is ideally designed for researchers, statisticians, academicians, developers, scientists, practitioners, students, and educators seeking current research on the use of artificial neural networks in diagnosing and solving nonparametric problems.

Artificial Neural Networks for Modelling and Control of Non-Linear Systems

Author : Johan A.K. Suykens
Publisher : Springer Science & Business Media
ISBN 13 : 1475724934
Total Pages : 242 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Artificial Neural Networks for Modelling and Control of Non-Linear Systems by : Johan A.K. Suykens

Download or read book Artificial Neural Networks for Modelling and Control of Non-Linear Systems written by Johan A.K. Suykens and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks possess several properties that make them particularly attractive for applications to modelling and control of complex non-linear systems. Among these properties are their universal approximation ability, their parallel network structure and the availability of on- and off-line learning methods for the interconnection weights. However, dynamic models that contain neural network architectures might be highly non-linear and difficult to analyse as a result. Artificial Neural Networks for Modelling and Control of Non-Linear Systems investigates the subject from a system theoretical point of view. However the mathematical theory that is required from the reader is limited to matrix calculus, basic analysis, differential equations and basic linear system theory. No preliminary knowledge of neural networks is explicitly required. The book presents both classical and novel network architectures and learning algorithms for modelling and control. Topics include non-linear system identification, neural optimal control, top-down model based neural control design and stability analysis of neural control systems. A major contribution of this book is to introduce NLq Theory as an extension towards modern control theory, in order to analyze and synthesize non-linear systems that contain linear together with static non-linear operators that satisfy a sector condition: neural state space control systems are an example. Moreover, it turns out that NLq Theory is unifying with respect to many problems arising in neural networks, systems and control. Examples show that complex non-linear systems can be modelled and controlled within NLq theory, including mastering chaos. The didactic flavor of this book makes it suitable for use as a text for a course on Neural Networks. In addition, researchers and designers will find many important new techniques, in particular NLq emTheory, that have applications in control theory, system theory, circuit theory and Time Series Analysis.

Research Anthology on Artificial Neural Network Applications

Author : Management Association, Information Resources
Publisher : IGI Global
ISBN 13 : 1668424096
Total Pages : 1575 pages
Book Rating : 4.6/5 (684 download)

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Book Synopsis Research Anthology on Artificial Neural Network Applications by : Management Association, Information Resources

Download or read book Research Anthology on Artificial Neural Network Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2021-07-16 with total page 1575 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks (ANNs) present many benefits in analyzing complex data in a proficient manner. As an effective and efficient problem-solving method, ANNs are incredibly useful in many different fields. From education to medicine and banking to engineering, artificial neural networks are a growing phenomenon as more realize the plethora of uses and benefits they provide. Due to their complexity, it is vital for researchers to understand ANN capabilities in various fields. The Research Anthology on Artificial Neural Network Applications covers critical topics related to artificial neural networks and their multitude of applications in a number of diverse areas including medicine, finance, operations research, business, social media, security, and more. Covering everything from the applications and uses of artificial neural networks to deep learning and non-linear problems, this book is ideal for computer scientists, IT specialists, data scientists, technologists, business owners, engineers, government agencies, researchers, academicians, and students, as well as anyone who is interested in learning more about how artificial neural networks can be used across a wide range of fields.

Artificial Neural Networks

Author : Joao Luis Garcia Rosa
Publisher : BoD – Books on Demand
ISBN 13 : 9535127047
Total Pages : 416 pages
Book Rating : 4.5/5 (351 download)

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Book Synopsis Artificial Neural Networks by : Joao Luis Garcia Rosa

Download or read book Artificial Neural Networks written by Joao Luis Garcia Rosa and published by BoD – Books on Demand. This book was released on 2016-10-19 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: The idea of simulating the brain was the goal of many pioneering works in Artificial Intelligence. The brain has been seen as a neural network, or a set of nodes, or neurons, connected by communication lines. Currently, there has been increasing interest in the use of neural network models. This book contains chapters on basic concepts of artificial neural networks, recent connectionist architectures and several successful applications in various fields of knowledge, from assisted speech therapy to remote sensing of hydrological parameters, from fabric defect classification to application in civil engineering. This is a current book on Artificial Neural Networks and Applications, bringing recent advances in the area to the reader interested in this always-evolving machine learning technique.

Principles Of Artificial Neural Networks (2nd Edition)

Author : Daniel Graupe
Publisher : World Scientific
ISBN 13 : 9814475564
Total Pages : 320 pages
Book Rating : 4.8/5 (144 download)

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Book Synopsis Principles Of Artificial Neural Networks (2nd Edition) by : Daniel Graupe

Download or read book Principles Of Artificial Neural Networks (2nd Edition) written by Daniel Graupe and published by World Scientific. This book was released on 2007-04-05 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Artificial Higher Order Neural Networks for Modeling and Simulation

Author : Zhang, Ming
Publisher : IGI Global
ISBN 13 : 1466621761
Total Pages : 455 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Artificial Higher Order Neural Networks for Modeling and Simulation by : Zhang, Ming

Download or read book Artificial Higher Order Neural Networks for Modeling and Simulation written by Zhang, Ming and published by IGI Global. This book was released on 2012-10-31 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.

Artificial Intelligence in the Age of Neural Networks and Brain Computing

Author : Robert Kozma
Publisher : Academic Press
ISBN 13 : 0323958168
Total Pages : 398 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Artificial Intelligence in the Age of Neural Networks and Brain Computing by : Robert Kozma

Download or read book Artificial Intelligence in the Age of Neural Networks and Brain Computing written by Robert Kozma and published by Academic Press. This book was released on 2023-10-27 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. The book covers the major basic ideas of "brain-like computing" behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters. Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN Authored by top experts, global field pioneers, and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making Edited by high-level academics and researchers in intelligent systems and neural networks Includes all new chapters, including topics such as Frontiers in Recurrent Neural Network Research; Big Science, Team Science, Open Science for Neuroscience; A Model-Based Approach for Bridging Scales of Cortical Activity; A Cognitive Architecture for Object Recognition in Video; How Brain Architecture Leads to Abstract Thought; Deep Learning-Based Speech Separation and Advances in AI, Neural Networks