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Applied Linear Algebra and Optimization Using MATLAB
Author: Rizwan Butt
Publisher:
Published: 2011
Total Pages: 0
ISBN-13: 9781936420049
DOWNLOAD EBOOK →Accompanying CD-ROM contains ... "all of the figures, code, and m-files for all of the programs."--Page 4 of cover.
Linear Programming with MATLAB
Author: Michael C. Ferris
Publisher: SIAM
Published: 2007-01-01
Total Pages: 277
ISBN-13: 9780898718775
DOWNLOAD EBOOK →This textbook provides a self-contained introduction to linear programming using MATLAB software to elucidate the development of algorithms and theory. Early chapters cover linear algebra basics, the simplex method, duality, the solving of large linear problems, sensitivity analysis, and parametric linear programming. In later chapters, the authors discuss quadratic programming, linear complementarity, interior-point methods, and selected applications of linear programming to approximation and classification problems. Exercises are interwoven with the theory presented in each chapter, and two appendices provide additional information on linear algebra, convexity, nonlinear functions, and on available MATLAB commands, respectively. Readers can access MATLAB codes and associated mex files at a Web site maintained by the authors. Only a basic knowledge of linear algebra and calculus is required to understand this textbook, which is geared toward junior and senior-level undergraduate students, first-year graduate students, and researchers unfamiliar with linear programming.
Linear Programming Using MATLAB®
Author: Nikolaos Ploskas
Publisher: Springer
Published: 2017-10-28
Total Pages: 646
ISBN-13: 3319659197
DOWNLOAD EBOOK →This book offers a theoretical and computational presentation of a variety of linear programming algorithms and methods with an emphasis on the revised simplex method and its components. A theoretical background and mathematical formulation is included for each algorithm as well as comprehensive numerical examples and corresponding MATLAB® code. The MATLAB® implementations presented in this book are sophisticated and allow users to find solutions to large-scale benchmark linear programs. Each algorithm is followed by a computational study on benchmark problems that analyze the computational behavior of the presented algorithms. As a solid companion to existing algorithmic-specific literature, this book will be useful to researchers, scientists, mathematical programmers, and students with a basic knowledge of linear algebra and calculus. The clear presentation enables the reader to understand and utilize all components of simplex-type methods, such as presolve techniques, scaling techniques, pivoting rules, basis update methods, and sensitivity analysis.
Numerical Linear Algebra with Applications
Author: William Ford
Publisher: Academic Press
Published: 2014-09-14
Total Pages: 629
ISBN-13: 0123947847
DOWNLOAD EBOOK →Numerical Linear Algebra with Applications is designed for those who want to gain a practical knowledge of modern computational techniques for the numerical solution of linear algebra problems, using MATLAB as the vehicle for computation. The book contains all the material necessary for a first year graduate or advanced undergraduate course on numerical linear algebra with numerous applications to engineering and science. With a unified presentation of computation, basic algorithm analysis, and numerical methods to compute solutions, this book is ideal for solving real-world problems. The text consists of six introductory chapters that thoroughly provide the required background for those who have not taken a course in applied or theoretical linear algebra. It explains in great detail the algorithms necessary for the accurate computation of the solution to the most frequently occurring problems in numerical linear algebra. In addition to examples from engineering and science applications, proofs of required results are provided without leaving out critical details. The Preface suggests ways in which the book can be used with or without an intensive study of proofs. This book will be a useful reference for graduate or advanced undergraduate students in engineering, science, and mathematics. It will also appeal to professionals in engineering and science, such as practicing engineers who want to see how numerical linear algebra problems can be solved using a programming language such as MATLAB, MAPLE, or Mathematica. Six introductory chapters that thoroughly provide the required background for those who have not taken a course in applied or theoretical linear algebra Detailed explanations and examples A through discussion of the algorithms necessary for the accurate computation of the solution to the most frequently occurring problems in numerical linear algebra Examples from engineering and science applications
Linear Algebra And Optimization With Applications To Machine Learning - Volume Ii: Fundamentals Of Optimization Theory With Applications To Machine Learning
Author: Quaintance Jocelyn
Publisher: World Scientific
Published: 2020-03-16
Total Pages: 896
ISBN-13: 9811216584
DOWNLOAD EBOOK →Volume 2 applies the linear algebra concepts presented in Volume 1 to optimization problems which frequently occur throughout machine learning. This book blends theory with practice by not only carefully discussing the mathematical under pinnings of each optimization technique but by applying these techniques to linear programming, support vector machines (SVM), principal component analysis (PCA), and ridge regression. Volume 2 begins by discussing preliminary concepts of optimization theory such as metric spaces, derivatives, and the Lagrange multiplier technique for finding extrema of real valued functions. The focus then shifts to the special case of optimizing a linear function over a region determined by affine constraints, namely linear programming. Highlights include careful derivations and applications of the simplex algorithm, the dual-simplex algorithm, and the primal-dual algorithm. The theoretical heart of this book is the mathematically rigorous presentation of various nonlinear optimization methods, including but not limited to gradient decent, the Karush-Kuhn-Tucker (KKT) conditions, Lagrangian duality, alternating direction method of multipliers (ADMM), and the kernel method. These methods are carefully applied to hard margin SVM, soft margin SVM, kernel PCA, ridge regression, lasso regression, and elastic-net regression. Matlab programs implementing these methods are included.
Introduction to Applied Linear Algebra
Author: Stephen Boyd
Publisher: Cambridge University Press
Published: 2018-06-07
Total Pages: 477
ISBN-13: 1316518965
DOWNLOAD EBOOK →A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.
An Introduction to Applied Numerical Linear Algebra Using MATLAB
Author: Rizwan Butt
Publisher: Alpha Science International, Limited
Published: 2015
Total Pages: 0
ISBN-13: 9781783322022
DOWNLOAD EBOOK →Designed for engineers, mathematician, computer scientists, and physicists or for use as a textbook in computational courses, Applied Numerical Linear Algebra Using MATLAB, provides the reader with numerous applications, m-files, and practical examples to solve problems. Balancing theoretical concepts with computational speed and accuracy, the book includes numerous short programs in MATLAB that can be used to solve problems involving systems of linear equations, matrices, vectors, approximations, eigenvalue, computer graphics, and more. The author emphasizes the basic ideas of numerical techniques and the uses of modern mathematical software (MATLAB) rather than relying only on complex mathematical derivations. The book is accompanied by a CD-ROM with all the figures, codes, solutions, appendices, an introduction to MATLAB commands, and m-files for all the programs.
Introduction to Applied Linear Algebra with MATLAB
Author: Rizwan Butt
Publisher:
Published: 2008
Total Pages: 517
ISBN-13: 9783885384076
DOWNLOAD EBOOK →Applied Optimization with MATLAB Programming
Author: P. Venkataraman
Publisher: John Wiley & Sons
Published: 2009-03-23
Total Pages: 546
ISBN-13: 047008488X
DOWNLOAD EBOOK →Technology/Engineering/Mechanical Provides all the tools needed to begin solving optimization problems using MATLAB® The Second Edition of Applied Optimization with MATLAB® Programming enables readers to harness all the features of MATLAB® to solve optimization problems using a variety of linear and nonlinear design optimization techniques. By breaking down complex mathematical concepts into simple ideas and offering plenty of easy-to-follow examples, this text is an ideal introduction to the field. Examples come from all engineering disciplines as well as science, economics, operations research, and mathematics, helping readers understand how to apply optimization techniques to solve actual problems. This Second Edition has been thoroughly revised, incorporating current optimization techniques as well as the improved MATLAB® tools. Two important new features of the text are: Introduction to the scan and zoom method, providing a simple, effective technique that works for unconstrained, constrained, and global optimization problems New chapter, Hybrid Mathematics: An Application, using examples to illustrate how optimization can develop analytical or explicit solutions to differential systems and data-fitting problems Each chapter ends with a set of problems that give readers an opportunity to put their new skills into practice. Almost all of the numerical techniques covered in the text are supported by MATLAB® code, which readers can download on the text's companion Web site www.wiley.com/go/venkat2e and use to begin solving problems on their own. This text is recommended for upper-level undergraduate and graduate students in all areas of engineering as well as other disciplines that use optimization techniques to solve design problems.
