Text covers sets and mappings, vector spaces, matrices, linear functionals, other basics; plus linear programming, Tchebychev approximations, more. Ideal introduction for undergraduates; reference for theoretical, applied mathematicians. Problems and exercises.
Useful Concepts and Results at the Heart of Linear Algebra A one- or two-semester course for a wide variety of students at the sophomore/junior undergraduate level A Modern Introduction to Linear Algebra provides a rigorous yet accessible matrix-oriented introduction to the essential concepts of linear algebra. Concrete, easy-to-understand examples motivate the theory. The book first discusses vectors, Gaussian elimination, and reduced row echelon forms. It then offers a thorough introduction to matrix algebra, including defining the determinant naturally from the PA=LU factorization of a matrix. The author goes on to cover finite-dimensional real vector spaces, infinite-dimensional spaces, linear transformations, and complex vector spaces. The final chapter presents Hermitian and normal matrices as well as quadratic forms. Taking a computational, algebraic, and geometric approach to the subject, this book provides the foundation for later courses in higher mathematics. It also shows how linear algebra can be used in various areas of application. Although written in a "pencil and paper" manner, the text offers ample opportunities to enhance learning with calculators or computer usage. Solutions manual available for qualifying instructors
Ein Lehrbuch über die Theorie mit Blick auf die Praxis
Author: Jörg Liesen,Volker Mehrmann
Dies ist ein Lehrbuch für die klassische Grundvorlesung über die Theorie der Linearen Algebra mit einem Blick auf ihre modernen Anwendungen sowie historischen Notizen. Die Bedeutung von Matrizen wird dabei besonders betont. Die matrizenorientierte Darstellung führt zu einer besseren Anschauung und somit zu einem besseren intuitiven Verständnis und leichteren Umgang mit den abstrakten Objekten der Linearen Algebra. Zudem verdeutlicht sie die Bedeutung der Linearen Algebra als wichtiges Werkzeug in vielen Bereichen der Mathematik und ihren Anwendungen. Einige dieser Anwendungen werden in ausführlichen Beispielen im Buch diskutiert. In vielen "MATLAB-Minuten" können die Studierenden wichtige Sätze und Konzepte am Computer nachvollziehen. Alle notwendigen Vorkenntnisse werden in einer MATLAB-Kurzeinführung erläutert. Daneben gibt es über 300 Übungsaufgaben, die das Erlernen des Stoffes unterstützen.
Ward Cheney and David Kincaid have developed Linear Algebra: Theory and Applications, Second Edition, a multi-faceted introductory textbook, which was motivated by their desire for a single text that meets the various requirements for differing courses within linear algebra. For theoretically-oriented students, the text guides them as they devise proofs and deal with abstractions by focusing on a comprehensive blend between theory and applications. For application-oriented science and engineering students, it contains numerous exercises that help them focus on understanding and learning not only vector spaces, matrices, and linear transformations, but uses of software tools available for use in applied linear algebra. Using a flexible design, it is an ideal textbook for instructors who wish to make their own choice regarding what material to emphasis, and to accentuate those choices with homework assignments from a large variety of exercises, both in the text and online.
Linear Algebra constitutes a foundation course for those specializing in the fields of mathematics, engineering and science. The course normally takes one semester, but for those needing a more rigorous study of the subject, it involve up to two semesters.This book is based on the lecture notes given for the linear algebra course at the Department of Mathematics in Wuhan University.
Die Theorie der Linearen Algebra hat inzwischen die engen Grenzen geometrischer Problemstellungen weit hinter sich gelassen. In nahezu allen Gebieten der aktuellen Mathematik spielen heute Techniken der Linearen Algebra eine wichtige Rolle. Dieses Lehrbuch, das nun in einer zweiten überarbeiteten Auflage vorliegt, bietet eine systematische Einführung in die Lineare Algebra und entspricht in seinem stofflichen Umfang einer zweisemestrigen Anfängervorlesung, so wie sie an vielen Universitäten als Einführungsveranstaltung für Studierende mit Haupt- oder Nebenfach Mathematik sowie Studienziel Diplom oder Staatsexamen gehalten wird. Im Text wird besonderer Wert auf eine sorgfältige Entwicklung der in der Linearen Algebra gebräuchlichen Begriffsbildungen gelegt, wobei jedes Kapitel mit einer Darlegung der zugehörigen motivierenden geometrischen Ideen beginnt. Umfangreiches und direkt auf die einzelnen Themen bezogenes Übungsmaterial rundet die Darstellung ab.
As the basis of equations (and therefore problem-solving), linear algebra is the most widely taught sub-division of pure mathematics. Dr Allenby has used his experience of teaching linear algebra to write a lively book on the subject that includes historical information about the founders of the subject as well as giving a basic introduction to the mathematics undergraduate. The whole text has been written in a connected way with ideas introduced as they occur naturally. As with the other books in the series, there are many worked examples.
Linear Algebra and Matrix Analysis for Statistics offers a gradual exposition to linear algebra without sacrificing the rigor of the subject. It presents both the vector space approach and the canonical forms in matrix theory. The book is as self-contained as possible, assuming no prior knowledge of linear algebra. The authors first address the rudimentary mechanics of linear systems using Gaussian elimination and the resulting decompositions. They introduce Euclidean vector spaces using less abstract concepts and make connections to systems of linear equations wherever possible. After illustrating the importance of the rank of a matrix, they discuss complementary subspaces, oblique projectors, orthogonality, orthogonal projections and projectors, and orthogonal reduction. The text then shows how the theoretical concepts developed are handy in analyzing solutions for linear systems. The authors also explain how determinants are useful for characterizing and deriving properties concerning matrices and linear systems. They then cover eigenvalues, eigenvectors, singular value decomposition, Jordan decomposition (including a proof), quadratic forms, and Kronecker and Hadamard products. The book concludes with accessible treatments of advanced topics, such as linear iterative systems, convergence of matrices, more general vector spaces, linear transformations, and Hilbert spaces.
"Linear Algebra" is intended for a one-term course at the junior or senior level. It begins with an exposition of the basic theory of vector spaces and proceeds to explain the fundamental structure theorem for linear maps, including eigenvectors and eigenvalues, quadratic and hermitian forms, diagnolization of symmetric, hermitian, and unitary linear maps and matrices, triangulation, and Jordan canonical form. The book also includes a useful chapter on convex sets and the finite-dimensional Krein-Milman theorem. The presentation is aimed at the student who has already had some exposure to the elementary theory of matrices, determinants and linear maps. However the book is logically self-contained. In this new edition, many parts of the book have been rewritten and reorganized, and new exercises have been added.
This text introduces linear algebra-boiled to its essence-presented in a clear and concise fashion. Designed around a single-semester undergraduate course, Essential Linear Algebra introduces key concepts, various real-world applications, and provides detailed yet understandable proofs of key results that are aimed towards students with no advanced preparation in proof writing. The level of sophistication gradually increases from beginning to end in order to prepare students for subsequent studies.
Basic textbook covers theory of matrices and its applications to systems of linear equations and related topics such as determinants, eigenvalues, and differential equations. Includes numerous exercises.
Linear Algebra is an important part of pure mathematics, and is needed for applications in every part of mathematics, natural science and economics. However, the applications are not so obvious as those of calculus. Therefore, one must study Linear Algebra as pure mathematics, even if one is only interested in applications. Most students find the subject difficult because it is abstract. Many texts try to avoid the difficulty by emphasizing calculations and suppressing the mathematical content of the subject. This text proceeds from the view that it is best to present the difficulties honestly, but as concisely and simply as possible. Although the text is shorter than others, all the material of a semester course is included. In addition, there are sections on least squares approximation and factor analysis; and a final chapter presents the matrix factorings that are used in Numerical Analysis.
Praise for the First Edition ". . .recommended for the teacher and researcher as well as for graduate students. In fact, [it] has a place on every mathematician′s bookshelf." –American Mathematical Monthly Linear Algebra and Its Applications, Second Edition presents linear algebra as the theory and practice of linear spaces and linear maps with a unique focus on the analytical aspects as well as the numerous applications of the subject. In addition to thorough coverage of linear equations, matrices, vector spaces, game theory, and numerical analysis, the Second Edition features student–friendly additions that enhance the book′s accessibility, including expanded topical coverage in the early chapters, additional exercises, and solutions to selected problems. Beginning chapters are devoted to the abstract structure of finite dimensional vector spaces, and subsequent chapters address convexity and the duality theorem as well as describe the basics of normed linear spaces and linear maps between normed spaces. Further updates and revisions have been included to reflect the most up–to–date coverage of the topic, including: The QR algorithm for finding the eigenvalues of a self–adjoint matrix The Householder algorithm for turning self–adjoint matrices into tridiagonal form The compactness of the unit ball as a criterion of finite dimensionality of a normed linear space Additionally, eight new appendices have been added and cover topics such as: the Fast Fourier Transform; the spectral radius theorem; the Lorentz group; the compactness criterion for finite dimensionality; the characterization of commentators; proof of Liapunov′s stability criterion; the construction of the Jordan Canonical form of matrices; and Carl Pearcy′s elegant proof of Halmos′ conjecture about the numerical range of matrices. Clear, concise, and superbly organized, Linear Algebra and Its Applications, Second Edition serves as an excellent text for advanced undergraduate– and graduate–level courses in linear algebra. Its comprehensive treatment of the subject also makes it an ideal reference or self–study for industry professionals.
David Poole’s innovative book emphasizes vectors and geometric intuition from the start and better prepares students to make the transition from the computational aspects of the course to the theoretical. Designed for a one- or two-semester introductory course and written in simple, mathematical English Poole focuses his approach on benefiting student visualization and connection to the material. He offers concrete examples to engage the student before presenting abstraction, and immediately follows up theoretical discussion with further examples and an array of applications from a variety of disciplines. Students from a variety of backgrounds and learning styles benefit from Poole’s practical approach, which covers vectors and vector geometry early in order to enable students to visualize the mathematics while they are doing matrix operations. With a concrete understanding of vector geometry, students are able to visualize and understand the meaning of the calculations that they will encounter and develop mathematical maturity for thinking abstractly. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
This book provides students with the rudiments of Linear Algebra, a fundamental subject for students in all areas of science and technology. The book would also be good for statistics students studying linear algebra. It is the translation of a successful textbook currently being used in Italy. The author is a mathematician sensitive to the needs of a general audience. In addition to introducing fundamental ideas in Linear Algebra through a wide variety of interesting examples, the book also discusses topics not usually covered in an elementary text (e.g. the "cost" of operations, generalized inverses, approximate solutions). The challenge is to show why the "everyone" in the title can find Linear Algebra useful and easy to learn. The translation has been prepared by a native English speaking mathematician, Professor Anthony V. Geramita.
This solutions manual for Lang’s Undergraduate Analysis provides worked-out solutions for all problems in the text. They include enough detail so that a student can fill in the intervening details between any pair of steps.
Based on lectures given at Claremont McKenna College, this text constitutes a substantial, abstract introduction to linear algebra. The presentation emphasizes the structural elements over the computational - for example by connecting matrices to linear transformations from the outset - and prepares the student for further study of abstract mathematics. Uniquely among algebra texts at this level, it introduces group theory early in the discussion, as an example of the rigorous development of informal axiomatic systems.
This book discusses fundamental ideas of linear algebra. The author presents the spectral theory of nonselfadjoint matrix operators and matrix pencils in a finite dimensional Euclidean space. Statements of computational problems and brief descriptions of numerical algorithms, some of them nontraditional, are given. Proved in detail are classical problems that are not usually found in standard university courses. In particular, the material shows the role of delicate estimates for the resolvent of an operator and underscores the need for the study and use of such estimates in numerical analysis.