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This course is essential for college students taking Linear Algebra who want to learn both theory and application. Each lesson in the course begins with essential ideas & proofs before concluding with many worked-out examples. Theorems are stated and used but not proved to keep the emphasis on problem solving and gaining an intuitive feeling for the concepts.

English | Sep. 25, 1987 | ISBN: 0521310415 | 160 Pages | PDF | 949.72 KB

This is a short, readable introduction to basic linear algebra, as usually encountered in a first course. The development of the subject is integrated with a large number of worked examples that illustrate the ideas and methods.

WEB-Rip | MKV | VP6A @ 500 Kbit/s | 672x608 | MP3 Stereo @ 128 Kbit/s 44 KHz | 23 Hours 32 min | 12.3 GB

Professor Raffi Hovasapian covers Educator's Linear Algebra course with topics spanning everything from Matrices to Eigenvectors. Each lesson begins with essential theory and is anchored with many worked-out examples. Other topics in this fully self-contained Linear Algebra course include Determinants, Linear Transformations, Homogeneous Systems, and Orthogonal Complements. Professor Hovasapian combines his triple degrees in Mathematics, Chemistry, and Classics with his 10+ years of teaching experience to help students understand difficult mathematical concepts.

Springer | Mathematics | December 22, 2015 | ISBN-10: 3319243446 | 324 pages | pdf | 3.67 mb

by Jörg Liesen (Author), Volker Mehrmann (Author)

Improves intuition for students in their first contact with abstract concepts

Analyzes detailed examples from application, contains ‘MATLAB-Minutes’ and special topics from applied linear algebra

English | 1 July 1994 | ISBN: 0412552809 | 240 Pages | PDF | 4 MB

This volume presents a thorough discussion of systems of linear equations and their solutions. Vectors and matrices are introduced as required and an account of determinants is given. Great emphasis has been placed on keeping the presentation as simple as possible, with many illustrative examples.

ISBN: 0534936660 | edition 1995 | PDF | 554 pages | 67 mb

This book is an introduction to the ideas and the techniques of linear algebra directed to students of first or second course who already have the theory of linear algebra, the resolution of problems and the possible applications, and all of it maintaining an excelent level, step by step. This is a wonderful and easy to follow book about linear algebra. After reading this book with clear concept establishment, you might go ahead more advanced books.

English | 1992 | ISBN: 0198534361 , 0198534353 | ISBN-13: 9780198534365 , 9780198534358 | 376 pages | PDF | 6,9 MB

Every student of mathematics needs a sound grounding in the techniques of linear algebra. It forms the basis of the study of linear equations, matrices, linear mappings, and differential equations, and comprises a central part of any course in mathematics. This textbook provides a rigorous introduction to the main concepts of linear algebra which will be suitable for all students coming to the subject for the first time.

English | 1983 | ISBN: 0387907874, 0387975861 | 257 pages | PDF | 4 MB

Linear Algebra Through Geometry introduces the concepts of linear algebra through the careful study of two and three-dimensional Euclidean geometry. This approach makes it possible to start with vectors, linear transformations, and matrices in the context of familiar plane geometry and to move directly to topics such as dot products, determinants, eigenvalues, and quadratic forms.

English | Feb 1994 | ISBN: 0534936660 | 554 Pages | PDF | 67 MB

This text achieves a balance among computational skills, theories and applications of linear algebra. The contents can be arranged to allow for the presentation of a traditional introduction to linear algebra or a more applied course. More than 330 solved examples are included; many are computational and devoted to applications.

English | 2005 | ISBN: 0471735795 | 278 Pages | DJVU | 1 MB

Learn to write programs to solve linear algebraic problems The Second Edition of this popular textbook provides a highly accessible introduction to the numerical solution of linear algebraic problems.

Language: English | PDF | ISBN-10: 0470432055 | 2010 | 792 pages | 32 MB

Elementary Linear Algebra 10th edition gives an elementary treatment of linear algebra that is suitable for a first course for undergraduate students. The aim is to present the fundamentals of linear algebra in the clearest possible way; pedagogy is the main consideration. Calculus is not a prerequisite, but there are clearly labeled exercises and examples (which can be omitted without loss of continuity) for students who have studied calculus. Technology also is not required, but for those who would like to use MATLAB, Maple, or Mathematica, or calculators with linear algebra capabilities, exercises are included at the ends of chapters that allow for further exploration using those tools.

English | 2008 | ISBN: 0073532355 | 416 pages | PDF | 5,7 MB

Linear Algebra with Applications is an introductory text targeted to second or advanced first year undergraduates in engineering or mathematics. The organization of this text is motivated by the authors' experience which tells them what essential concepts should be mastered by students in a one semester undergraduate Linear Algebra course.

English | pages: 390 | 2004 | ISBN: 0817642943 | scan PDF | 27 mb

This second edition includes substantial revisions, new material on minimal polynomials and diagonalization, as well as a variety of new applications. The text will serve theoretical and applied courses and is ideal for self-study. With its important approach to linear algebra as a coherent part of mathematics and as a vital component of the natural and social sciences, Linear Algebra, Second Edition will challenge and benefit a broad audience.

English | 2008 | ISBN: 1584887826 | 752 pages | PDF | 7,3 MB

Linear Algebra: A First Course with Applications explores the fundamental ideas of linear algebra, including vector spaces, subspaces, basis, span, linear independence, linear transformation, eigenvalues, and eigenvectors, as well as a variety of applications, from inventories to graphics to Google’s PageRank.