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Schaum's Outline of Theory and Problems of Matrix Operations

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Unlike the Schaum's outline of linear algebra, which is more about the physical interpretation of matrices as vectors, this Schaum's outline is good for learning techniques of solutions that were meant for large matrices. It is aimed at the applied mathematician, since there are not very many proofs as exercises. Instead, the user is taught the various algorithms used to solve matrix problems. The guide starts with very basic operations such as matrix addition, subtraction, and dot products. It then moves on to methods of solution for finding the determinant, eigenvalues and eigenvectors, and the functions of a matrix. What I particularly like about this guide is that in its more advanced section it shows in plain language how to implement singular value decomposition, the QR algorithm to compute eigenvalues, vector norms, LU decomposition, and other more advanced methods of solution that are not mentioned in basic linear algebra texts and are overloaded with theory in more advanced texts that lack practical examples. This book is an excellent companion to texts such as Trefethen and Bau's "Numerical Linear Algebra", since that book is short on worked examples and concentrates more on theory. The format of this guide is the same of most other Schaum's outlines- for each topic there are a few pages on motivation and the algorithms themselves, a section of worked problems, and a section of more problems with answers but not with complete solutions.

This is a very nice book that covers a everything one needs to know about matrices, without the extra derivations and confusion associated with this math. Very nice examples are included in the book that show the use of matrices.

If you do, this book is very helpful in that it gives a step-by-step approach to solving matrix operations problems. Although I wouldn't use this book by itself, I would recommend getting this to supplement the class. If you have already taken the class, then this is a good refresher or reference for you.

The topics covered are inversions, determinants, vectors, eigenvalues and eigenvectors, functions, square matrices, hermitian and positive definite matrices, canonical bases, unitary transformations, and nonnegative and patterned matrices, among other topics. As with other books in the Schaum's series, there are supplementary questions to test your knowledge and understanding. Most of the answers are in the back.

Great book for review of linear algebra. I needed this book to check the results of code I had written for a quadratic beta routine.

Takes you right from the basics to complex stuff like QR decomposition and SVD. Very useful for programmers who want to gain knowledge on solving linear equations.

The author has a real knack at making the subject accessible and easy to assimilate. I would recommend you get this book before you go on to a more advanced book like Matrix Computations (Johns Hopkins Studies in Mathematical Sciences)(3rd Edition).
You can read this bit by bit, there are plenty of examples to drive the point home and it's easy to find what you are looking for. All this for a very low price. What more could you ask? Well, sure there could be more advanced topics, Householder matrices are only touched upon, but you'll pick that up easily when you are done with this book.

Matrices permeate modern industrial societies. There is hardly a single branch of science and engineering where they don't play an important role. From matrix (quantum) mechanics to marketing, from numerical analysis to neurosciences all depend, to some extent, on matrices to express their concepts. No wonder an authoritative and comprehensive book on elementary matrix theory was to be greatly desired. Many have been published over the years, but few worthy of note.

Most physics and engineering students long for an easy-to-study math book to hone their problem-solving skills. Professor Richard Branson's book "Matrix Operations" helps them to do just that, and much more. His innovative algorithmic approach -concise and compact- to matrix theory demystify a subject that often haunts college students. Chapters follow a logical sequence where matrix algebra and matrix (numerical) methods live side by side in perfect harmony. Without losing sight of mathematical rigour, Professor Branson presents simultaneous linear equations, matrix inversion, eigenvalues and eigenvectors, inner products, canonical bases, similarity, Hermitian matrices, quadratic forms and the like in a most successful manner. His exposition of Jordan canonical forms (on pp.91-93, chapter 10), crème de la crème of the theory, is a jewel of simplicity (if the great French mathematician Camille Jordan were still alive he would certainly be proud of it). Rather involved topics such as the Cholesky decomposition, finite Markov chains, and Rayleigh's principle were cut to the bone; and esoteric mathematical entities such as Gerschgorin disk (on page 170, chapter 19) rendered more tasteful to the palate through Branson's magic touch. I wish a book like this had been available in my college years. Happiness came too late.

I got this book to try to make up for not haven taken linear algebra in school, because I am trying to learn to program in MatLab, whose name is derived from Matrix Labratory! So it works out, ie the book, to be a decent review for something I never actually studied!

This is a very nice book to supplement almost any linear/matrix algebra book you may have. Nice to see some proofs written out for some of the exercises. For the incredible low price, you can't go wrong with this. However, I would highly recommend beginners to learn from a standard linear algebra textbook first before diving into this. My only complaint is that for some of the more advanced topics, it doesn't go far enough. Maybe someone can write a Advanced Matrix Operations sequel some day.

The text book was in excellent condition and arrived in a timely fashion.
I recommend this book seller.