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Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering
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Fuzzy Neural Networks for Real Time Control Applications - Concepts, Modeling and Algorithms for Fast Learning (Paperback)
Loot Price: R1,875
Discovery Miles 18 750
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Fuzzy Neural Networks for Real Time Control Applications - Concepts, Modeling and Algorithms for Fast Learning (Paperback)
Expected to ship within 12 - 17 working days
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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.
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