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270016597
MATLAB for ENGINEERING and EXPERIMENTAL SCIENCES: PROGRAMMING and OPTIMIZATION
Item #:
270016597
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- This book introduces techniques programming and optimization through MATLAB. It begins by introducing the MATLAB environment and the structure of MATLAB programming before moving on to the mathematics necessary for optimization tasks. These tasks are introduced sequentially in order of technical difficulty. Algorithms are developed for numerical derivation and integration, as well as for the resolution of differential equations. The central part of the book is dedicated to MATLAB’s Optimization Techniques. The Optimization Toolbox includes algorithms for solving multiobjective problems, non-linear minimization with boundary conditions and restrictions, minimax optimization, semi-infinitely constrained minimization and linear and quadratic programming. Routines for solving linear and quadratic programming problems use an active-set method combined with imaging techniques. The routines provide a range of algorithms and linear research strategies. Linear search strategies are protected methods of quadratic and cubic interpolation and extrapolation. Symbolic mathematics methods for optimization are also considered. A wide range of exercises are included, illustrating techniques such as linear programming, quadratic programming, non-linear least-squares and the solution of non-linear equations. These topics are augmented with examples that put into practice the most widely used optimization methods.
| Publisher | Scientific Books |
| Publication date | September 25, 2021 |
| Language | English |
| Print length | 259 pages |
| ISBN-10 | 1716128994 |
| ISBN-13 | 978-1716128998 |
| Item Weight | 1.72 pounds (780 grams) |
| Dimensions | 8.27 x 0.59 x 11.69 inches (21 x 1.5 x 29.7 cm) |
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MATLAB for ENGINEERING and EXPERIMENTAL SCIENCES: PROGRAMMING and OPTIMIZATION
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Features & Benefits
- Comprehensive introduction to MATLAB programming and optimization techniques.
- Sequential learning of optimization tasks from easy to complex levels.
- Focus on MATLAB’s Optimization Toolbox for diverse algorithms.
- Includes methods for multiobjective problems and non-linear minimization.
- Practical exercises to reinforce optimization methodologies.
- Real-world examples demonstrate the application of advanced optimization techniques.
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