Oxford linear algebra for scientists, Lukas, Andre (professor Of Theoretical Physics, Professor Of Theoretical Physics, University Of Oxford)
Автор: Strang Название: Differential Equations and Linear Algebra ISBN: 0980232791 ISBN-13(EAN): 9780980232790 Издательство: Cambridge Academ Рейтинг: Цена: 60180.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Differential equations and linear algebra are two central topics in the undergraduate mathematics curriculum. This innovative textbook allows the two subjects to be developed either separately or together, illuminating the connections between two fundamental topics, and giving increased flexibility to instructors. It can be used either as a semester-long course in differential equations, or as a one-year course in differential equations, linear algebra, and applications. Beginning with the basics of differential equations, it covers first and second order equations, graphical and numerical methods, and matrix equations. The book goes on to present the fundamentals of vector spaces, followed by eigenvalues and eigenvectors, positive definiteness, integral transform methods and applications to PDEs. The exposition illuminates the natural correspondence between solution methods for systems of equations in discrete and continuous settings. The topics draw on the physical sciences, engineering and economics, reflecting the author's distinguished career as an applied mathematician and expositor.
Автор: Trefethen, Lloyd N. Bau, David, Iii Название: Numerical linear algebra ISBN: 0898713617 ISBN-13(EAN): 9780898713619 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 64370.00 T Наличие на складе: Поставка под заказ. Описание: Numerical Linear Algebra is a concise, insightful, and elegant introduction to the field of numerical linear algebra.
Автор: Wolfgang Wechler Название: Universal Algebra for Computer Scientists ISBN: 3642767737 ISBN-13(EAN): 9783642767739 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A new model-theoretic approach to universal algebra is offered in this book. The book concerns the algebraic characterization of axiomatic classes of algebras (equational, implicational, and universal Horn classes) by closure operators generalizing the famous Birkhoff Variety Theorem, and the algebraic characterization of the related theories.
Автор: Roman Название: Advanced Linear Algebra ISBN: 0387728287 ISBN-13(EAN): 9780387728285 Издательство: Springer Рейтинг: Цена: 54210.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Details the basics of linear algebra. This book discusses modules, emphasizing a comparison with vector spaces. It also discusses inner product spaces, eigenvalues, eigenvectors, finite dimensional spectral theory and finite dimensional spectral theorem for normal operators.
Автор: Hardy Yorick, Steeb Willi-Hans Название: Matrix Calculus, Kronecker Product and Tensor Product: A Practical Approach to Linear Algebra, Multilinear Algebra and Tensor Calculus with Software I ISBN: 9811202516 ISBN-13(EAN): 9789811202513 Издательство: World Scientific Publishing Рейтинг: Цена: 95040.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Our self-contained volume provides an accessible introduction to linear and multilinear algebra as well as tensor calculus. Besides the standard techniques for linear algebra, multilinear algebra and tensor calculus, many advanced topics are included where emphasis is placed on the Kronecker product and tensor product. The Kronecker product has widespread applications in signal processing, discrete wavelets, statistical physics, Hopf algebra, Yang-Baxter relations, computer graphics, fractals, quantum mechanics, quantum computing, entanglement, teleportation and partial trace. All these fields are covered comprehensively.The volume contains many detailed worked-out examples. Each chapter includes useful exercises and supplementary problems. In the last chapter, software implementations are provided for different concepts. The volume is well suited for pure and applied mathematicians as well as theoretical physicists and engineers.New topics added to the third edition are: mutually unbiased bases, Cayley transform, spectral theorem, nonnormal matrices, Gateaux derivatives and matrices, trace and partial trace, spin coherent states, Clebsch-Gordan series, entanglement, hyperdeterminant, tensor eigenvalue problem, Carleman matrix and Bell matrix, tensor fields and Ricci tensors, and software implementations.
Автор: Savov Ivan Название: No Bullshit Guide to Linear Algebra ISBN: 0992001021 ISBN-13(EAN): 9780992001025 Издательство: Неизвестно Рейтинг: Цена: 35870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Linear algebra is the foundation of science and engineering. Knowledge of linear algebra is a prerequisite for studying statistics, machine learning, computer graphics, signal processing, chemistry, economics, quantum mechanics, and countless other applications. Indeed, linear algebra offers a powerful toolbox for modelling the real world.
The No Bullshit Guide to Linear Algebra shows the connections between the computational techniques of linear algebra, their geometric interpretations, and the theoretical foundations. This university-level textbook contains lessons on linear algebra written in a style that is precise and concise. Each concept is illustrated through definitions, formulas, diagrams, explanations, and examples of real-world applications. Readers build their math superpowers by solving practice problems and learning to use the computer algebra system SymPy to speed up tedious matrix arithmetic tasks.
"The book explains the concepts in a way that gives a strong intuitive understanding." - Joe Nestor, student
"It's very well written and a fun read " - Felix Kwok, professor
"I used this book in multiple big data courses when I needed a deeper understanding of the material." - Zane Zakraisek, student
The author, Ivan Savov, combines 17 years of tutoring experience with a B.Eng. in electrical engineering, an M.Sc. in physics, and a Ph.D. in computer science from McGill University.
Автор: Strang, Gilbert Название: Introduction to linear algebra ISBN: 1733146652 ISBN-13(EAN): 9781733146654 Издательство: Cambridge Academ Рейтинг: Цена: 79190.00 T Наличие на складе: Невозможна поставка. Описание: Linear algebra is something all mathematics undergraduates and many other students, in subjects ranging from engineering to economics, have to learn. The fifth edition of this hugely successful textbook retains the quality of earlier editions while at the same time seeing numerous minor improvements and major additions. The latter include: a new chapter on singular values and singular vectors, including ways to analyze a matrix of data; a revised chapter on computing in linear algebra, with professional-level algorithms and code that can be downloaded for a variety of languages; a new section on linear algebra and cryptography; and a new chapter on linear algebra in probability and statistics. A dedicated and active website also offers solutions to exercises as well as new exercises from many different sources (e.g. practice problems, exams, development of textbook examples), plus codes in MATLAB, Julia, and Python.
Автор: von zur Gathen Название: Modern Computer Algebra ISBN: 1107039037 ISBN-13(EAN): 9781107039032 Издательство: Cambridge Academ Рейтинг: Цена: 117210.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Designed to accompany one- or two-semester courses for advanced undergraduate or graduate students, this textbook is widely regarded as the `bible of computer algebra`. Its comprehensiveness and reliability also makes it an essential reference for professionals. This updated edition includes an overview of recent improvements in areas like primality testing.
Автор: Mora Название: Solving Polynomial Equation Systems IV ISBN: 1107109639 ISBN-13(EAN): 9781107109636 Издательство: Cambridge Academ Рейтинг: Цена: 182690.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In this fourth and final volume the author covers extensions of Buchberger`s Algorithm, including a discussion of the most promising recent alternatives to Groebner bases: Gerdt`s involutive bases and Faugere`s F4 and F5 algorithms. This completes the author`s comprehensive treatise, which is a fundamental reference for any mathematical library.
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.
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