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Introduction to Nonlinear Optimization Theory, Algorithms, and Applications with MATLAB : MOS-SIAM Series on Optimization - Amir Beck

Introduction to Nonlinear Optimization Theory, Algorithms, and Applications with MATLAB

By: Amir Beck

Paperback | 30 October 2014

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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.
  • Several subjects not typically found in optimization books - for example, optimality conditions in sparsity-constrained optimization, hidden convexity, and total least squares.
  • 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.
  • 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.
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