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Author : Christian Eitzinger
Publisher :
ISBN 13 :
Total Pages : 164 pages
Book Rating : 4.90/5 ( download)
Download or read book Second-order and Nonsmooth Training Methods for Fuzzy Neural Networks written by Christian Eitzinger and published by . This book was released on 2001 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Adrian J. Shepherd
Publisher : Springer Science & Business Media
ISBN 13 : 1447109538
Total Pages : 156 pages
Book Rating : 4.32/5 ( download)
Download or read book Second-Order Methods for Neural Networks written by Adrian J. Shepherd and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: About This Book This book is about training methods - in particular, fast second-order training methods - for multi-layer perceptrons (MLPs). MLPs (also known as feed-forward neural networks) are the most widely-used class of neural network. Over the past decade MLPs have achieved increasing popularity among scientists, engineers and other professionals as tools for tackling a wide variety of information processing tasks. In common with all neural networks, MLPsare trained (rather than programmed) to carryout the chosen information processing function. Unfortunately, the (traditional' method for trainingMLPs- the well-knownbackpropagation method - is notoriously slow and unreliable when applied to many prac tical tasks. The development of fast and reliable training algorithms for MLPsis one of the most important areas ofresearch within the entire field of neural computing. The main purpose of this book is to bring to a wider audience a range of alternative methods for training MLPs, methods which have proved orders of magnitude faster than backpropagation when applied to many training tasks. The book also addresses the well-known (local minima' problem, and explains ways in which fast training methods can be com bined with strategies for avoiding (or escaping from) local minima. All the methods described in this book have a strong theoretical foundation, drawing on such diverse mathematical fields as classical optimisation theory, homotopic theory and stochastic approximation theory.
Author : Erdal Kayacan
Publisher : Butterworth-Heinemann
ISBN 13 : 0128027037
Total Pages : 264 pages
Book Rating : 4.35/5 ( download)
Download or read book Fuzzy Neural Networks for Real Time Control Applications written by Erdal Kayacan and published by Butterworth-Heinemann. This book was released on 2015-10-07 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: AN INDISPENSABLE RESOURCE FOR ALL THOSE WHO DESIGN AND IMPLEMENT TYPE-1 AND TYPE-2 FUZZY NEURAL NETWORKS IN REAL TIME SYSTEMS Delve into the type-2 fuzzy logic systems and become engrossed in the parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis with this book! Not only does this book stand apart from others in its focus but also in its application-based presentation style. Prepared in a way that can be easily understood by those who are experienced and inexperienced in this field. Readers can benefit from the computer source codes for both identification and control purposes which are given at the end of the book. A clear and an in-depth examination has been made of all the necessary mathematical foundations, type-1 and type-2 fuzzy neural network structures and their learning algorithms as well as their stability analysis. You will find that each chapter is devoted to a different learning algorithm for the tuning of type-1 and type-2 fuzzy neural networks; some of which are: • Gradient descent • Levenberg-Marquardt • Extended Kalman filter In addition to the aforementioned conventional learning methods above, number of novel sliding mode control theory-based learning algorithms, which are simpler and have closed forms, and their stability analysis have been proposed. Furthermore, hybrid methods consisting of particle swarm optimization and sliding mode control theory-based algorithms have also been introduced. The potential readers of this book are expected to be the undergraduate and graduate students, engineers, mathematicians and computer scientists. Not only can this book be used as a reference source for a scientist who is interested in fuzzy neural networks and their real-time implementations but also as a course book of fuzzy neural networks or artificial intelligence in master or doctorate university studies. We hope that this book will serve its main purpose successfully. Parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis Contains algorithms that are applicable to real time systems Introduces fast and simple adaptation rules for type-1 and type-2 fuzzy neural networks Number of case studies both in identification and control Provides MATLAB® codes for some algorithms in the book
Author : Stamatios V. Kartalopoulos
Publisher : Wiley-IEEE Press
ISBN 13 :
Total Pages : 240 pages
Book Rating : 4.58/5 ( download)
Download or read book Understanding Neural Networks and Fuzzy Logic written by Stamatios V. Kartalopoulos and published by Wiley-IEEE Press. This book was released on 1996 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand the fundamentals of the emerging field of fuzzy neural networks, their applications and the most used paradigms with this carefully organized state-of-the-art textbook. Previously tested at a number of noteworthy conference tutorials, the simple numerical examples presented in this book provide excellent tools for progressive learning. UNDERSTANDING NEURAL NETWORKS AND FUZZY LOGIC offers a simple presentation and bottom-up approach that is ideal for working professional engineers, undergraduates, medical/biology majors, and anyone with a nonspecialist background. Sponsored by: IEEE Neural Networks Council
Author : Somnath Bhattacharyya
Publisher : Springer Nature
ISBN 13 : 9811536155
Total Pages : 497 pages
Book Rating : 4.51/5 ( download)
Download or read book Mathematical Modeling and Computational Tools written by Somnath Bhattacharyya and published by Springer Nature. This book was released on 2020-04-20 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features original research papers presented at the International Conference on Computational and Applied Mathematics, held at the Indian Institute of Technology Kharagpur, India during November 23–25, 2018. This book covers various topics under applied mathematics, ranging from modeling of fluid flow, numerical techniques to physical problems, electrokinetic transport phenomenon, graph theory and optimization, stochastic modelling and machine learning. It introduces the mathematical modeling of complicated scientific problems, discusses micro- and nanoscale transport phenomena, recent development in sophisticated numerical algorithms with applications, and gives an in-depth analysis of complicated real-world problems. With contributions from internationally acclaimed academic researchers and experienced practitioners and covering interdisciplinary applications, this book is a valuable resource for researchers and students in fields of mathematics, statistics, engineering, and health care.
Author : Anne-Johan Annema
Publisher : Springer Science & Business Media
ISBN 13 : 0792395670
Total Pages : 256 pages
Book Rating : 4.76/5 ( download)
Download or read book Feed-Forward Neural Networks written by Anne-Johan Annema and published by Springer Science & Business Media. This book was released on 1995-05-31 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Feed-Forward Neural Networks: Vector Decomposition Analysis, Modelling and Analog Implementation presents a novel method for the mathematical analysis of neural networks that learn according to the back-propagation algorithm. The book also discusses some other recent alternative algorithms for hardware implemented perception-like neural networks. The method permits a simple analysis of the learning behaviour of neural networks, allowing specifications for their building blocks to be readily obtained. Starting with the derivation of a specification and ending with its hardware implementation, analog hard-wired, feed-forward neural networks with on-chip back-propagation learning are designed in their entirety. On-chip learning is necessary in circumstances where fixed weight configurations cannot be used. It is also useful for the elimination of most mis-matches and parameter tolerances that occur in hard-wired neural network chips. Fully analog neural networks have several advantages over other implementations: low chip area, low power consumption, and high speed operation. Feed-Forward Neural Networks is an excellent source of reference and may be used as a text for advanced courses.
Author :
Publisher :
ISBN 13 :
Total Pages : 1096 pages
Book Rating : 4.50/5 ( download)
Download or read book Smart Engineering System Design written by and published by . This book was released on 2001 with total page 1096 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jing Na
Publisher : Academic Press
ISBN 13 : 0128136847
Total Pages : 336 pages
Book Rating : 4.43/5 ( download)
Download or read book Adaptive Identification and Control of Uncertain Systems with Non-smooth Dynamics written by Jing Na and published by Academic Press. This book was released on 2018-06-12 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Identification and Control of Uncertain Systems with Nonsmooth Dynamics reports some of the latest research on modeling, identification and adaptive control for systems with nonsmooth dynamics (e.g., backlash, dead zone, friction, saturation, etc). The authors present recent research results for the modelling and control designs of uncertain systems with nonsmooth dynamics, such as friction, dead-zone, saturation and hysteresis, etc., with particular applications in servo systems. The book is organized into 19 chapters, distributed in five parts concerning the four types of nonsmooth characteristics, namely friction, dead-zone, saturation and hysteresis, respectively. Practical experiments are also included to validate and exemplify the proposed approaches. This valuable resource can help both researchers and practitioners to learn and understand nonlinear adaptive control designs. Academics, engineers and graduate students in the fields of electrical engineering, control systems, mechanical engineering, applied mathematics and computer science can benefit from the book. It can be also used as a reference book on adaptive control for servo systems for students with some background in control engineering. Explains the latest research outputs on modeling, identification and adaptive control for systems with nonsmooth dynamics Provides practical application and experimental results for robotic systems, and servo motors
Author : Madan Gupta
Publisher : Wiley-IEEE Press
ISBN 13 : 0471460923
Total Pages : 752 pages
Book Rating : 4.23/5 ( download)
Download or read book Static and Dynamic Neural Networks written by Madan Gupta and published by Wiley-IEEE Press. This book was released on 2004-04-05 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides comprehensive treatment of the theory of both static and dynamic neural networks. * Theoretical concepts are illustrated by reference to practical examples Includes end-of-chapter exercises and end-of-chapter exercises. *An Instructor Support FTP site is available from the Wiley editorial department.
Author : Chi-hau Chen
Publisher : McGraw-Hill Companies
ISBN 13 :
Total Pages : 862 pages
Book Rating : 4.92/5 ( download)
Download or read book Fuzzy Logic and Neural Network Handbook written by Chi-hau Chen and published by McGraw-Hill Companies. This book was released on 1996 with total page 862 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical reference that presents concise and comprehensive reports on the major activities in fuzzy logic and neural networks, with emphasis on the applications and systems of interest to computer engineers. Each of the 31 chapters focuses on the most important activity of a specific topic, and the chapters are organized into three parts: principles and algorithms; applications; and architectures and systems. The applications for fuzzy logic include home appliance design and manufacturing process; those for neural networks include radar, sonar, and speech signal processing, remote sensing, and electrical power systems. Annotation copyright by Book News, Inc., Portland, OR
