| 書目名稱 | Linear Algebra for Pattern Processing | | 副標題 | Projection, Singular | | 編輯 | Kenichi Kanatani | | 視頻video | http://file.papertrans.cn/587/586279/586279.mp4 | | 叢書名稱 | Synthesis Lectures on Signal Processing | | 圖書封面 |  | | 描述 | Linear algebra is one of the most basic foundations of a wide range of scientific domains, and most textbooks of linear algebra are written by mathematicians. However, this book is specifically intended to students and researchers of pattern information processing, analyzing signals such as images and exploring computer vision and computer graphics applications. The author himself is a researcher of this domain.Such pattern information processing deals with a large amount of data, which are represented by high-dimensional vectors and matrices. There, the role of linear algebra is not merely numerical computation of large-scale vectors and matrices. In fact, data processing is usually accompanied with "geometric interpretation." For example, we can think of one data set being "orthogonal" to another and define a "distance" between them or invoke geometric relationships such as "projecting" some data onto some space. Such geometric concepts not only help us mentally visualize abstracthigh-dimensional spaces in intuitive terms but also lead us to find what kind of processing is appropriate for what kind of goals.First, we take up the concept of "projection" of linear spaces and descri | | 出版日期 | Book 2021 | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-02544-0 | | isbn_softcover | 978-3-031-01416-1 | | isbn_ebook | 978-3-031-02544-0Series ISSN 1932-1236 Series E-ISSN 1932-1694 | | issn_series | 1932-1236 | | copyright | Springer Nature Switzerland AG 2021 |
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