Numerical linear algebra and optimization /, Gill, Philip E.,
Автор: Nocedal, Jorge. Название: Numerical Optimization ISBN: 0387303030 ISBN-13(EAN): 9780387303031 Издательство: Springer Рейтинг: Цена: 71080.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Optimization is an important tool used in decision science and for the analysis of physical systems used in engineering. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.
Автор: Boyd Stephen Название: Introduction to Applied Linear Algebra ISBN: 1316518965 ISBN-13(EAN): 9781316518960 Издательство: Cambridge Academ Рейтинг: Цена: 45410.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A groundbreaking introductory textbook covering the linear algebra methods needed for data science and engineering applications. It combines straightforward explanations with numerous practical examples and exercises from data science, machine learning and artificial intelligence, signal and image processing, navigation, control, and finance.
Автор: Arak M. Mathai, Hans J. Haubold Название: Linear Algebra: A Course for Physicists and Engineers ISBN: 3110562359 ISBN-13(EAN): 9783110562354 Издательство: Walter de Gruyter Цена: 53250.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In order not to intimidate students by a too abstract approach, this textbook on linear algebra is written to be easy to digest by non-mathematicians. It introduces the concepts of vector spaces and mappings between them without dwelling on statements such as theorems and proofs too much. It is also designed to be self-contained, so no other material is required for an understanding of the topics covered. As the basis for courses on space and atmospheric science, remote sensing, geographic information systems, meteorology, climate and satellite communications at UN-affiliated regional centers, various applications of the formal theory are discussed as well. These include differential equations, statistics, optimization and some engineering-motivated problems in physics. ContentsVectorsMatricesDeterminantsEigenvalues and eigenvectorsSome applications of matrices and determinantsMatrix series and additional properties of matrices
This book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied mathematics, and electrical engineering. By only assuming a knowledge of calculus, the authors develop, in a rigorous yet down to earth manner, the mathematical theory behind concepts such as: vectors spaces, bases, linear maps, duality, Hermitian spaces, the spectral theorems, SVD, and the primary decomposition theorem. At all times, pertinent real-world applications are provided. This book includes the mathematical explanations for the tools used which we believe that is adequate for computer scientists, engineers and mathematicians who really want to do serious research and make significant contributions in their respective fields.
Автор: Quaintance Jocelyn, Gallier Jean H Название: Linear Algebra And Optimization With Applications To Machine Learning - Volume Ii: Fundamentals Of Optimization Theory With Applications To Machine Learning ISBN: 9811216568 ISBN-13(EAN): 9789811216565 Издательство: World Scientific Publishing Рейтинг: Цена: 190080.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 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.
Автор: Gallier Jean H, Quaintance Jocelyn Название: Linear Algebra And Optimization With Applications To Machine Learning - Volume I: Linear Algebra For Computer Vision, Robotics, And Machine Learning ISBN: 9811206392 ISBN-13(EAN): 9789811206399 Издательство: World Scientific Publishing Рейтинг: Цена: 190080.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied mathematics, and electrical engineering. By only assuming a knowledge of calculus, the authors develop, in a rigorous yet down to earth manner, the mathematical theory behind concepts such as: vectors spaces, bases, linear maps, duality, Hermitian spaces, the spectral theorems, SVD, and the primary decomposition theorem. At all times, pertinent real-world applications are provided. This book includes the mathematical explanations for the tools used which we believe that is adequate for computer scientists, engineers and mathematicians who really want to do serious research and make significant contributions in their respective fields.
"This book is suitable as a textbook for an introductory undergraduate mathematics course on discrete Fourier and wavelet transforms for students with background in calculus and linear algebra. The particular strength of this book is its accessibility to students with no background in analysis. The exercises and computer explorations provide the reader with many opportunities for active learning. Studying from this text will also help students strengthen their background in linear algebra."
Mathematical Association of America
This textbook for undergraduate mathematics, science, and engineering students introduces the theory and applications of discrete Fourier and wavelet transforms using elementary linear algebra, without assuming prior knowledge of signal processing or advanced analysis.
It explains how to use the Fourier matrix to extract frequency information from a digital signal and how to use circulant matrices to emphasize selected frequency ranges. It introduces discrete wavelet transforms for digital signals through the lifting method and illustrates through examples and computer explorations how these transforms are used in signal and image processing. Then the general theory of discrete wavelet transforms is developed via the matrix algebra of two-channel filter banks. Finally, wavelet transforms for analog signals are constructed based on filter bank results already presented, and the mathematical framework of multiresolution analysis is examined.
"This book is suitable as a textbook for an introductory undergraduate mathematics course on discrete Fourier and wavelet transforms for students with background in calculus and linear algebra. The particular strength of this book is its accessibility to students with no background in analysis. The exercises and computer explorations provide the reader with many opportunities for active learning. Studying from this text will also help students strengthen their background in linear algebra."
Mathematical Association of America
This textbook for undergraduate mathematics, science, and engineering students introduces the theory and applications of discrete Fourier and wavelet transforms using elementary linear algebra, without assuming prior knowledge of signal processing or advanced analysis.
It explains how to use the Fourier matrix to extract frequency information from a digital signal and how to use circulant matrices to emphasize selected frequency ranges. It introduces discrete wavelet transforms for digital signals through the lifting method and illustrates through examples and computer explorations how these transforms are used in signal and image processing. Then the general theory of discrete wavelet transforms is developed via the matrix algebra of two-channel filter banks. Finally, wavelet transforms for analog signals are constructed based on filter bank results already presented, and the mathematical framework of multiresolution analysis is examined.
Автор: Gr?goire Allaire; K. Trabelsi; Sidi Mahmoud Kaber Название: Numerical Linear Algebra ISBN: 1489997415 ISBN-13(EAN): 9781489997418 Издательство: Springer Рейтинг: Цена: 46540.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book distinguishes itself from the many other textbooks on the topic of linear algebra by including mathematical and computational chapters along with examples and exercises with Matlab. Here, the authors use both Matlab and SciLab software as well as covering core standard material.
Автор: Gene H. Golub; Paul Van Dooren Название: Numerical Linear Algebra, Digital Signal Processing and Parallel Algorithms ISBN: 3642755380 ISBN-13(EAN): 9783642755385 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Proceedings of the NATO Advanced Study Institute on Numerical Linear Algebra, Digital Signal Processing and Parallel Algorithms, held in Leuven, Belgium, August 1-12, 1988
Автор: Wendland Holger Название: Numerical Linear Algebra ISBN: 131660117X ISBN-13(EAN): 9781316601174 Издательство: Cambridge Academ Рейтинг: Цена: 40120.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This self-contained introduction to numerical linear algebra provides a comprehensive, yet concise, overview of the subject. This book will be of particular use to applied mathematicians, engineers, computer scientists, and to all those interested in efficiently solving linear problems.
Автор: Bornemann, Folkmar Название: Numerical linear algebra ISBN: 3319742213 ISBN-13(EAN): 9783319742212 Издательство: Springer Рейтинг: Цена: 51230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Preface.- I Computing with Matrices.- II Matrix Factorization.- III Error Analysis.- IV Least Squares.- V Eigenvalue Problems.- Appendix.- Notation.- Index.
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