Fuzzy Neural Networks for Real Time Control Applications

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  • Author : Erdal Kayacan
  • Publisher : Butterworth-Heinemann
  • Pages : 264 pages
  • ISBN : 9780128026878
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Fuzzy Neural Networks for Real Time Control Applications

Download or Read online Fuzzy Neural Networks for Real Time Control Applications full in PDF, ePub and kindle. this book written by Erdal Kayacan and published by Butterworth-Heinemann which was released on 17 September 2015 with total page 264 pages. We cannot guarantee that Fuzzy Neural Networks for Real Time Control Applications book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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

Fuzzy Neural Networks for Real Time Control Applications

Fuzzy Neural Networks for Real Time Control Applications
  • Author : Erdal Kayacan,Mojtaba Ahmadieh Khanesar
  • Publisher : Butterworth-Heinemann
  • Release : 17 September 2015
GET THIS BOOK Fuzzy Neural Networks for Real Time Control Applications

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

Fuzzy Neural Networks for Real Time Control Applications

Fuzzy Neural Networks for Real Time Control Applications
  • Author : Erdal Kayacan,Mojtaba Ahmadieh Khanesar
  • Publisher : Butterworth-Heinemann
  • Release : 07 October 2015
GET THIS BOOK Fuzzy Neural Networks for Real Time Control Applications

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

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  • Publisher : Springer
  • Release : 31 January 2017
GET THIS BOOK Design of Interpretable Fuzzy Systems

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  • Publisher : Springer
  • Release : 23 August 2018
GET THIS BOOK Biologically Inspired Cognitive Architectures 2018

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  • Publisher : Springer
  • Release : 10 June 2019
GET THIS BOOK Fuzzy Techniques Theory and Applications

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  • Publisher : Springer Nature
  • Release : 17 August 2020
GET THIS BOOK Soft Computing Applications

This book presents the proceedings of the 8th International Workshop on Soft Computing Applications, SOFA 2018, held on 13–15 September 2018 in Arad, Romania. The workshop was organized by Aurel Vlaicu University of Arad, in conjunction with the Institute of Computer Science, Iasi Branch of the Romanian Academy, IEEE Romanian Section, Romanian Society of Control Engineering and Technical Informatics – Arad Section, General Association of Engineers in Romania – Arad Section and BTM Resources Arad. The papers included in these proceedings, published post-conference, cover the

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  • Author : Jerry M. Mendel
  • Publisher : Springer
  • Release : 17 May 2017
GET THIS BOOK Uncertain Rule Based Fuzzy Systems

The second edition of this textbook provides a fully updated approach to fuzzy sets and systems that can model uncertainty — i.e., “type-2” fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications from time-series forecasting to knowledge mining to control. In this new edition, a bottom-up approach is presented that begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can

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  • Author : A. Crespo
  • Publisher : Elsevier
  • Release : 28 June 2014
GET THIS BOOK Artificial Intelligence in Real Time Control 1994

Artificial Intelligence is one of the new technologies that has contributed to the successful development and implementation of powerful and friendly control systems. These systems are more attractive to end-users shortening the gap between control theory applications. The IFAC Symposia on Artificial Intelligence in Real Time Control provides the forum to exchange ideas and results among the leading researchers and practitioners in the field. This publication brings together the papers presented at the latest in the series and provides a

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  • Publisher : Elsevier
  • Release : 28 June 2014
GET THIS BOOK Artificial Intelligence in Real Time Control 1992

The symposium had two main aims, to investigate the state-of-the-art in the application of artificial intelligence techniques in real-time control, and to bring together control system specialists, artificial intelligence specialists and end-users. Many professional engineers working in industry feel that the gap between theory and practice in applying control and systems theory is widening, despite efforts to develop control algorithms. Papers presented at the meeting ranged from the theoretical aspects to the practical applications of artificial intelligence in real-time control.

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  • Author : L. Almeida,Luis B. Almeida,S. Boverie
  • Publisher : Elsevier
  • Release : 22 January 2022
GET THIS BOOK Intelligent Components and Instruments for Control Applications 2003 SICICA 2003

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  • Publisher : John Wiley & Sons
  • Release : 30 March 2015
GET THIS BOOK Contemporary Issues in Systems Science and Engineering

Various systems science and engineering disciplines are covered and challenging new research issues in these disciplines are revealed. They will be extremely valuable for the readers to search for some new research directions and problems. Chapters are contributed by world-renowned systems engineers Chapters include discussions and conclusions Readers can grasp each event holistically without having professional expertise in the field

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  • Publisher : Springer
  • Release : 12 March 2018
GET THIS BOOK Artificial Intelligence in Renewable Energetic Systems

This book includes the latest research presented at the International Conference on Artificial Intelligence in Renewable Energetic Systems held in Tipaza, Algeria on October 22–24, 2017. The development of renewable energy at low cost must necessarily involve the intelligent optimization of energy flows and the intelligent balancing of production, consumption and energy storage. Intelligence is distributed at all levels and allows information to be processed to optimize energy flows according to constraints. This thematic is shaping the outlines of future economies of

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  • Publisher : Elsevier
  • Release : 23 May 2014
GET THIS BOOK Algorithms and Architectures for Real Time Control 1992

This Workshop focuses on such issues as control algorithms which are suitable for real-time use, computer architectures which are suitable for real-time control algorithms, and applications for real-time control issues in the areas of parallel algorithms, multiprocessor systems, neural networks, fault-tolerance systems, real-time robot control identification, real-time filtering algorithms, control algorithms, fuzzy control, adaptive and self-tuning control, and real-time control applications.

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GET THIS BOOK Introduction to Deep Learning for Engineers

This book provides a short introduction and easy-to-follow implementation steps of deep learning using Google Cloud Platform. It also includes a practical case study that highlights the utilization of Python and related libraries for running a pre-trained deep learning model. In recent years, deep learning-based modeling approaches have been used in a wide variety of engineering domains, such as autonomous cars, intelligent robotics, computer vision, natural language processing, and bioinformatics. Also, numerous real-world engineering applications utilize an existing pre-trained deep