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Titlebook: Linear Functions and Matrix Theory; Bill Jacob TextbookLatest edition Springer Science+Business Media New York 1995 Eigenvalue.Eigenvector

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書目名稱Linear Functions and Matrix Theory
編輯Bill Jacob
視頻videohttp://file.papertrans.cn/587/586323/586323.mp4
叢書名稱Encyclopaedia of Mathematical Sciences
圖書封面Titlebook: Linear Functions and Matrix Theory;  Bill Jacob TextbookLatest edition Springer Science+Business Media New York 1995 Eigenvalue.Eigenvector
描述Courses that study vectors and elementary matrix theory and introduce linear transformations have proliferated greatly in recent years. Most of these courses are taught at the undergraduate level as part of, or adjacent to, the second-year calculus sequence. Although many students will ultimately find the material in these courses more valuable than calculus, they often experience a class that consists mostly of learning to implement a series of computational algorithms. The objective of this text is to bring a different vision to this course, including many of the key elements called for in current mathematics-teaching reform efforts. Three of the main components of this current effort are the following: 1. Mathematical ideas should be introduced in meaningful contexts, with formal definitions and procedures developed after a clear understanding of practical situations has been achieved. 2. Every topic should be treated from different perspectives, including the numerical, geometric,and symbolic viewpoints. 3. The important ideas need to be visited repeatedly throughout the term, with students‘ understanding deepening each time. This text was written with these three objectives in
出版日期TextbookLatest edition
關(guān)鍵詞Eigenvalue; Eigenvector; Matrix; Matrix Theory; linear algebra
版次1
doihttps://doi.org/10.1007/978-3-642-59277-5
issn_series 0938-0396
copyrightSpringer Science+Business Media New York 1995
The information of publication is updating

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Eigenvalues and Eigenvectors of Matrices,Throughout this chapter we will consider square matrices only. We shall see that many properties of an . × . matrix . can be understood by determining which (if any) vectors . ∈ .. satisfy .for some real number ..
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