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Titlebook: Matrix Operations for Engineers and Scientists; An Essential Guide i Alan Jeffrey Textbook 2010 Springer Science+Business Media B.V. 2010 E

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發(fā)表于 2025-3-21 18:10:30 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Matrix Operations for Engineers and Scientists
副標(biāo)題An Essential Guide i
編輯Alan Jeffrey
視頻videohttp://file.papertrans.cn/628/627763/627763.mp4
概述Carefully explains each operation with matrices and offers many worked examples to show how to use these operations.Provides exercises with each chapter - solutions at the end of the book.Explains how
圖書封面Titlebook: Matrix Operations for Engineers and Scientists; An Essential Guide i Alan Jeffrey Textbook 2010 Springer Science+Business Media B.V. 2010 E
描述Engineers and scientists need to have an introduction to the basics of linear algebra in a context they understand. Computer algebra systems make the manipulation of matrices and the determination of their properties a simple matter, and in practical applications such software is often essential. However, using this tool when learning about matrices, without first gaining a proper understanding of the underlying theory, limits the ability to use matrices and to apply them to new problems. This book explains matrices in the detail required by engineering or science students, and it discusses linear systems of ordinary differential equations. These students require a straightforward introduction to linear algebra illustrated by applications to which they can relate. It caters of the needs of undergraduate engineers in all disciplines, and provides considerable detail where it is likely to be helpful.According to the author the best way to understand the theory of matrices is by working simple exercises designed to emphasize the theory, that at the same time avoid distractions caused by unnecessary numerical calculations. Hence, examples and exercises in this book have been constructe
出版日期Textbook 2010
關(guān)鍵詞Eigenvalue; Eigenvector; Matrix; algebra; computer algebra; computer algebra system; linear algebra; linear
版次1
doihttps://doi.org/10.1007/978-90-481-9274-8
isbn_softcover978-90-481-9273-1
isbn_ebook978-90-481-9274-8
copyrightSpringer Science+Business Media B.V. 2010
The information of publication is updating

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Matrix Multiplication, the Inverse Matrix and Partitioning,Matrix multiplication is based on the product . of an . element row vector . = [.., .., ..] and an . element column vector . = [.., .., ..].. This product of vectors written ., and called the . or . of the matrix row vector . and the matrix column vector ., is defined as
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https://doi.org/10.1007/978-90-481-9274-8Eigenvalue; Eigenvector; Matrix; algebra; computer algebra; computer algebra system; linear algebra; linear
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Determinants, and Linear Independence,ar systems of algebraic equations, in the formal definition of an inverse matrix, and in the study of the eigenvalues of a matrix. So, in anticipation of what is to follow in later chapters, and before developing the properties of determinants in general, we will introduce and motivate their study b
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