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Titlebook: Essential Student Algebra; Volume Two: Matrices T. S. Blyth,E. F. Robertson Book 1986 T. S. Blyth and E. F. Robertson 1986 Eigenvalue.Eigen

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發(fā)表于 2025-3-21 18:10:20 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Essential Student Algebra
副標(biāo)題Volume Two: Matrices
編輯T. S. Blyth,E. F. Robertson
視頻videohttp://file.papertrans.cn/316/315545/315545.mp4
圖書(shū)封面Titlebook: Essential Student Algebra; Volume Two: Matrices T. S. Blyth,E. F. Robertson Book 1986 T. S. Blyth and E. F. Robertson 1986 Eigenvalue.Eigen
描述H, as it is often said, mathematics is the queen of science then algebra is surely the jewel in her crown. In the course of its vast development over the last half-century, algebra has emerged as the subject in which one can observe pure mathe- matical reasoning at its best. Its elegance is matched only by the ever-increasing number of its applications to an extraordinarily wide range of topics in areas other than ‘pure‘ mathematics. Here our objective is to present, in the form of a series of five concise volumes, the fundamentals of the subject. Broadly speaking, we have covered in all the now traditional syllabus that is found in first and second year university courses, as well as some third year material. Further study would be at the level of ‘honours options‘. The reasoning that lies behind this modular presentation is simple, namely to allow the student (be he a mathematician or not) to read the subject in a way that is more appropriate to the length, content, and extent, of the various courses he has to take. Although we have taken great pains to include a wide selec- tion of illustrative examples, we have not included any exer- cises. For a suitable companion collection o
出版日期Book 1986
關(guān)鍵詞Eigenvalue; Eigenvector; algebra; matrices; matrix; science
版次1
doihttps://doi.org/10.1007/978-94-017-2213-1
isbn_softcover978-0-412-27870-9
isbn_ebook978-94-017-2213-1
copyrightT. S. Blyth and E. F. Robertson 1986
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沙發(fā)
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地板
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Construction de Series Discretes p-adiquesWe shall now give brief descriptions of some situations to which matrix theory finds a natural application, and some problems to which the solutions are determined by the algebra we have developed. Some of these applications will be dealt with in greater detail later.
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Leslie P. Steffe,Ernst von GlasersfeldWe shall now consider in detail a systematic method of solving systems of linear equations. In working with such systems, there are three basic operations involved, namely
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https://doi.org/10.1007/978-3-030-55108-7In 1.3 we showed that every . × . matrix . has an additive inverse, denoted by — ., which is the unique . × . matrix . such that . + . = 0. In this Chapter we consider the multiplicative analogue of this for square matrices.
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Construction of Lyapunov Functions,In order to proceed further with matrices we have to take a wider view of matters. This we do through the following important notion.
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https://doi.org/10.1007/978-3-658-35999-7In what follows it will prove convenient to write an . × . matrix . in the form.where, as before, the notation a. represents the .-th column of .. Also, the letter . will signify as usual either the field IR of real numbers or the field ? of complex numbers.
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