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Titlebook: Partial Differential Equations; Jürgen Jost Textbook 20021st edition Springer Science+Business Media New York 2002 Maximum.PDE.Partial Dif

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書(shū)目名稱(chēng)Partial Differential Equations
編輯Jürgen Jost
視頻videohttp://file.papertrans.cn/742/741465/741465.mp4
叢書(shū)名稱(chēng)Graduate Texts in Mathematics
圖書(shū)封面Titlebook: Partial Differential Equations;  Jürgen Jost Textbook 20021st edition Springer Science+Business Media New York 2002 Maximum.PDE.Partial Dif
描述This textbook is intended for students who wish to obtain an introduction to the theory of partial di?erential equations (PDEs, for short), in particular, those of elliptic type. Thus, it does not o?er a comprehensive overview of the whole ?eld of PDEs, but tries to lead the reader to the most important methods and central results in the case of elliptic PDEs. The guiding qu- tion is how one can ?nd a solution of such a PDE. Such a solution will, of course, depend on given constraints and, in turn, if the constraints are of the appropriate type, be uniquely determined by them. We shall pursue a number of strategies for ?nding a solution of a PDE; they can be informally characterized as follows: (0) Write down an explicit formula for the solution in terms of the given data (constraints). This may seem like the best and most natural approach, but this is possible only in rather particular and special cases. Also, such a formula may be rather complicated, so that it is not very helpful for detecting qualitative properties of a solution. Therefore, mathematical analysis has developed other, more powerful, approaches. (1) Solve a sequence of auxiliary problems that approximate the given
出版日期Textbook 20021st edition
關(guān)鍵詞Maximum; PDE; Partial Differential Equations; Sobolev space; calculus; differential equation; hyperbolic e
版次1
doihttps://doi.org/10.1007/b97312
isbn_ebook978-0-387-21595-2Series ISSN 0072-5285 Series E-ISSN 2197-5612
issn_series 0072-5285
copyrightSpringer Science+Business Media New York 2002
The information of publication is updating

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year approximately 37.3 million elderly worldwide experience a fall event that is severe enough to require medical attention. This research proposes a system for activity assessment and fall detection intended for in-home applications using the Internet of Things (IoT) for real-time detection of fa
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