Fuzzy Logic
Multi-Sensor Data Fusion with MATLAB
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Title:
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Multi-Sensor Data Fusion with MATLAB
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Authors:
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Jitendra R. Raol
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Edition:
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2009
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Publisher:
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CRC Press
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Pages:
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568
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Language:
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English
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ISBN-10
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1439800030
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ISBN-13
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978-1439800034
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Format:
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PDF + MATLAB programs (ZIP)
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Size (MB):
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8 | |
Book Description:
Fusing sensors’ data can lead to numerous benefits in a system’s performance. Through real-world examples and the evaluation of algorithmic results, this detailed book provides an understanding of MSDF concepts and methods from a practical point of view. Table of Contents: Fuzzy Logic and Decision Fusion, J.R. Raol and S.K. Kashyap Pixel and Feature-Level Image Fusion, J.R. Raol and V.P.S. Naidu A Brief on Data Fusion in Other Systems, Ajith Gopal and Simukai Utete Copyright Disclaimer: |
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Fuzzy Systems Engineering: Theory and Practice
Book Description
This book is devoted to reporting innovative and significant progress in fuzzy system engineering. Given the maturation of fuzzy logic, this book is dedicated to exploring the recent breakthroughs in fuzziness and soft computing in favor of intelligent system engineering. This monograph presents novel developments of the fuzzy theory as well as interesting applications of the fuzzy logic exploiting the theory to engineer intelligent systems.
Table of Contents
Part I Fuzzy Theory.
Introducing You to Fuzziness.
A Qualitative Approach for Symbolic Data Manipulation Under Uncertainty.
Adaptation of Fuzzy Inference System Using Neural Learning.
Part II Fuzzy Systems.
A fuzzy approach on guiding model for interception flight.
On the Stability and Sensitivity Analysis of Fuzzy Control Systems for Servo-systems.
Applications of Fuzzy Logic in Mobile Robots Control.
Modeling the Tennessee Eastman Chemical Process Reactor Using Fuzzy Logic.
Download
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Fuzzy Control and Identification
Book Description
This book gives an introduction to basic fuzzy logic and Mamdani and Takagi-Sugeno fuzzy systems. The text shows how these can be used to control complex nonlinear engineering systems, while also also suggesting several approaches to modeling of complex engineering systems with unknown models.
Finally, fuzzy modeling and control methods are combined in the book, to create adaptive fuzzy controllers, ending with an example of an obstacle-avoidance controller for an autonomous vehicle using modus ponendo tollens logic.
Table of Contents
CHAPTER 1 INTRODUCTION.
CHAPTER 2 BASIC CONCEPTS OF FUZZY SETS.
CHAPTER 3 MAMDANI FUZZY SYSTEMS.
CHAPTER 4 FUZZY CONTROL WITH MAMDANI SYSTEMS.
CHAPTER 5 MODELING AND CONTROL METHODS USEFUL FOR FUZZY CONTROL.
CHAPTER 6 TAKAGI–SUGENO FUZZY SYSTEMS.
CHAPTER 7 PARALLEL DISTRIBUTED CONTROL WITH TAKAGI–SUGENO FUZZY SYSTEMS.
CHAPTER 8 ESTIMATION OF STATIC NONLINEAR FUNCTIONS FROM DATA.
CHAPTER 9 MODELING OF DYNAMIC PLANTS AS FUZZY SYSTEMS.
CHAPTER 10 ADAPTIVE FUZZY CONTROL.
Download
You can download this book from any of the following links. If any link is dead please feel free to leave a comment.
LINK 1
LINK 2
LINK 3
Copyright Disclaimer
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we’ll remove relevant links or contents immediately.