Robotics, Vision and Control:. Fundamental Algorithms in MATLAB
Practical Theory Signals with MATLAB Applications.
PID and Predictive Control of Electrical Drives and Power Converters Using MATLAB / Simulink.
MATLAB Control Systems Engineering.
Introduction to MATLAB for Engineers, 3rd Edition.
Discrete Systems and Digital Signal Processing with MATLAB.
Advanced Mathematics and Mechanics Applications Using MATLAB 3rd edition.
Digital Image Processing Using MATLAB (2nd Edition).
PSPICE and MATLAB for Electronics: An Integrated Approach, 2nd edition.
Matlab: A Practical Introduction to Programming and Problem Solving.
Signals and Systems with MATLAB Primer.
Image Processing. Tensor Transform and Discrete Tomography with MATLAB
Numerical methods using MATLAB.
Modeling of Curves and Surfaces with MATLAB.
Numerical and Analytical Methods with MATLAB.
Digital Speech Processing Using Matlab.
Modeling and Simulation of Systems Using MATLAB.
Electrical Machines with MATLAB Second Edition.
What Every Engineer Should Know about MATLAB and Simulink.
Computational Partial Differential Equations Using MATLAB.
Computational Statistics Handbook with MATLAB, Second Edition.
Real-Time Digital Signal Processing from MATLAB to C with the TMS320C6x DSPs, Second Edition.
Mechanics of Composite Materials with MATLAB.
Digital Image Processing. An Algorithmic Approach with MATLAB
Computer Methods for Engineering Applications with MATLAB. – Second Edition
Solving Applied Mathematical Problems with MATLAB.
Introduction to Finite Element Methods and Spectral Using MATLAB, Second Edition 2nd Edition.
Introduction to Linear Optimization and Extensions with MATLAB.
Numerical Methods for Chemical Engineers Using Excel, VBA, and MATLAB.
MATLAB Programming for Numerical Analysis.
Neural Networks and Machine Learning (3rd Edition).
Optimal and Robust Control. Advanced Topics with MATLAB
MATLAB For Beginners: A Gentle Approach.
Space Electronic Recognition:. Localization Theories and Methods
Smart Antennas with MATLAB, Second Edition.
MATLAB with Applications to Engineering, Physics and Finance.
EEG signal processing.
Arduino programming with LabVIEW.
Digital Signal Processing Using MATLAB.
DSP for MATLAB and LabVIEW. I: Fundamentals of Discrete Signal Processing
LabVIEW for Engineers
MATLAB Codes for Finite Element Analysis. Solids and Structures
LabVIEW: A Developer’s Guide to Real World Integration by Ian Fairweather.
Principles of Neural Information Processing.
Learning to Program with MATLAB GUI Building Tools.
Intelligent Control Systems with LabVIEW.
Sparse Representations for Radar with MATLAB Examples.
MATLAB Matrix Algebra by Cesar Lopez.
LabVIEW: Advanced Programming Techniques, Second Edition.
Signals and Systems with MATLAB and Simulink Modeling Computing 4th edition.
Differential Equations and Mathematical Biology, Second Edition.
Image Processing with LabVIEW and IMAQ Vision.
MATLAB Demystified by David McMahon.
Introduction to Numerical Preliminaries with MATLAB.
Learning to Program with MATLAB GUI Building Tools.
MATLAB: An Introduction with Applications. 5th edition by Amos Gilat
2014 | ISBN: 1118629868 | ISBN-13: 9?81 1 18629864 | 416 pages I PDF | 31,5 MB
More college students use Amos Gilat’s MATLAB: An Introduction with Applications than any other
MATLAB textbook. This concise book is known for its just-in-time learning approach that gives
students information when they need it.
The new edition gradually presents the latest MATLAB functionality in detail. Equally effective as a
freshmen-level text. self-study tool, or course reference, the book is generously illustrated through
computer screen shots and step-by-step tutorials, with abundant and motivating applications to
problems in mathematics, science. and engineering.
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Using MATLABLEI examples wherever possible, Multi-Sensor Data Fusion with MATLAB explores the
three levels of multi-sensor data fusion {MSDF}: kinematic-level blend, including the theory of DF;
fuzzy logic and decision fusion; along with pixel- and feature-level image blend. The authors
elucidate DF techniques, algorithms, and performance evaluation generally for aerospace
applications, although the methods can even be applied to systems in other places. such as
biornedicine, military safeguard. and environmental engineering.
After representing several useful strategies and algorithms pertaining to DF and tracking
performance. this book evaluates DF algorithms, application, and systems. It next protects fuzzy
logic. fuzzy sets along with their properties. fuzzy logic operators, fuzzy propositionsfrule-based
systems. an inference serps, and defuzzification methods. It develops the latest MATi_AB graphical
user interface pertaining to evaluating fuzzy implication functions, before using fuzzy logic for you
to estimate the unknown states of your dynamic system by processing sensor info. The book then
employs main component analysis. spatial frequency. and wavelet-based image fusion algorithms
for the fusion of image data by sensors. it also presents procedures for combing tracks extracted
from imaging sensor and ground-based radar. The last chapters discuss how DF is put on mobile
intelligent autonomous systems along with intelligent monitoring systems.
Fusing sensors’ data can bring about numerous benefits in a system’s efficiency. Through real-
world examples and this evaluation of algorithmic results, this detailed book provides a
comprehension of MSDF concepts and methods from a practical point of view.
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