Sepe, W. Milic and Z. Bertsekas and John N. Friedberg , Arnold J. Insel , Lawrence E. Callister, Jr. Simon , Lawrence E. Schulz, Ajit D. Ahuja , Thomas L. Magnanti , James B. Steven C. I 6th Ed. II 6th Ed. Undeland, William P. Grainger William D. Viterbi and Jim K. Neftci, B. Yates , David J. Rehg, Glenn J. Roberts, M. Shampine, I. McCormac and Stephen F. Scott MacKenzie and Raphael C. Askeland, Pradeep P. Young, Roger A. Why this is marked as abuse?
It has been marked as abuse. Please try again. The work is protected by local and international copyright laws and is provided solely for the use of instructors in teaching their courses and assessing student learning. You have successfully signed out and will be required to sign back in should you need to download more resources. Overview Features Contents Order Overview. Description For courses in introductory linear algebra This title is part of the Pearson Modern Classics series.
Pearson Modern Classics are acclaimed titles at a value price. Please visit www. Series This product is part of the following series. An early introduction to vector space ideas—In Chapter 3, elementary vector space ideas subspace, basis, dimension, and so on are introduced in the familiar setting of Rn. An early introduction to eigenvalues—It is now possible with this text to cover the eigenvalue problem very early and in much greater depth.
A brief introduction to determinants is given in Section 4. An early introduction to linear combinations—In Section 1.
This viewpoint leads to a simple and natural development for the theory associated with systems of linear equations. This approach gives some early motivation for the vector space concepts introduced in Chapter 3 such as subspace, basis, and dimension. Applications to different fields of study—Provides motivation for students in a wide variety of disciplines. Hallmark Features A gradual increase in the level of difficulty. In a typical linear algebra course, students find the techniques of Gaussian elimination and matrix operations fairly easy.
Then, the ensuing material relating to vector spaces is suddenly much harder. The authors have done three things to lessen this abrupt midterm jump in difficulty: 1. Introduction of linear independence early, in Section 1. Introduction of vector space concepts such as subspace, basis and dimension in Chapter 3, in the familiar geometrical setting of Rn.
Clarity of exposition. For many students, linear algebra is the most rigorous and abstract mathematical course they have taken since high-school geometry. The authors have tried to write the text so that it is accessible, but also so that it reveals something of the power of mathematical abstraction. To this end, the topics have been organized so that they flow logically and naturally from the concrete and computational to the more abstract. Numerous examples, many presented in extreme detail, have been included in order to illustrate the concepts.
Supplementary exercises. A set of supplementary exercises are included at the end of each chapter. These exercises, some of which are true-false questions, are designed to test the student's understanding of important concepts.
They often require the student to use ideas from several different sections. Extensive exercise sets. Numerous exercises, ranging from routine drill exercises to interesting applications, and exercises of a theoretical nature. The more difficult theoretical exercises have fairly substantial hints.
0コメント