| 書目名稱 | Tensor Computation for Data Analysis | | 編輯 | Yipeng Liu,Jiani Liu,Ce Zhu | | 視頻video | http://file.papertrans.cn/904/903069/903069.mp4 | | 概述 | Provides a systematic and up-to-date overview of tensor decompositions from the engineer’s point of view.Includes an up-to-date coverage of tensor computation based data analysis methods.Discusses a n | | 圖書封面 |  | | 描述 | .Tensor is a natural representation for multi-dimensional data, and tensor computation can avoid possible multi-linear data structure loss in classical matrix computation-based data analysis. ..?.This book is intended to provide non-specialists an overall understanding of tensor computation and its applications in data analysis, and benefits researchers, engineers, and students with theoretical, computational, technical and experimental details. It presents a systematic and up-to-date overview of tensor decompositions from the engineer‘s point of view, and comprehensive coverage of tensor computation based data analysis techniques. In addition, some practical examples in machine learning, signal processing, data mining, computer vision, remote sensing, and biomedical engineering are also presented for easy understanding and implementation. These data analysis techniques may be further applied in other applications on neuroscience, communication, psychometrics, chemometrics, biometrics, quantum physics, quantum chemistry, etc..?.The discussion begins with basic coverage of notations, preliminary operations in tensor computations, main tensor decompositions and their properties. Base | | 出版日期 | Book 2022 | | 關(guān)鍵詞 | Tensors in Image Processing; Tensors in Computer Vision; Tensor Component Analysis; Matrix and Tensor V | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-74386-4 | | isbn_softcover | 978-3-030-74388-8 | | isbn_ebook | 978-3-030-74386-4 | | copyright | Springer Nature Switzerland AG 2022 |
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