Introduction to Nonlinear Optimization: Theory, Algorithms, and Applications with MATLAB (MOS-SIAM Series on Optimization) free ebook download.

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Introduction to Nonlinear Optimization: Theory, Algorithms, and Applications with MATLAB (MOS-SIAM Series on Optimization) free ebook download

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Algorithms

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Author(s):	Amir Beck

Date:	2014-10-27	Format:	pdf	Language:	English	ISBN/ASIN:	1611973643
Pages:	294	OCR:		Quality:		ISBN13:	9781611973648
Uploader:	eternal	Upload Date:	12/8/2017 10:21:14 AM

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This book provides the foundations of the theory of nonlinear optimization as well as some related algorithms and presents a variety of applications from diverse areas of applied sciences. The author combines three pillars of optimization-theoretical and algorithmic foundation, familiarity with various applications, and the ability to apply the theory and algorithms on actual problems-and rigorously and gradually builds the connection between theory, algorithms, applications, and implementation.

Readers will find more than 170 theoretical, algorithmic, and numerical exercises that deepen and enhance the reader's understanding of the topics. The author includes several subjects not typically found in optimization books-for example, optimality conditions in sparsity-constrained optimization, hidden convexity, and total least squares. The book also offers a large number of applications discussed theoretically and algorithmically, such as circle fitting, Chebyshev center, the Fermat-Weber problem, denoising, clustering, total least squares, and orthogonal regression and theoretical and algorithmic topics demonstrated by the MATLAB toolbox CVX and a package of m-files that is posted on the book's web site.

Audience: This book is intended for graduate or advanced undergraduate students of mathematics, computer science, and electrical engineering as well as other engineering departments. The book will also be of interest to researchers.

Contents: Chapter 1: Mathematical Preliminaries  Chapter 2: Optimality Conditions for Unconstrained Optimization  Chapter 3: Least Squares  Chapter 4: The Gradient Method  Chapter 5: Newton s Method  Chapter 6: Convex Sets  Chapter 7: Convex Functions  Chapter 8: Convex Optimization  Chapter 9: Optimization Over a Convex Set  Chapter 10: Optimality Conditions for Linearly Constrained Problems  Chapter 11: The KKT Conditions  Chapter 12: Duality

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2054196	part1	https://k2s.cc/file/7e2625813392b/161197...		30.00	eternal

Tags: Algorithms Applications Introduction MATLAB MOS-SIAM Nonlinear Optimization Theory

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