logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Tensors For Data Processing Theory Methods And Applications 1st Edition Yipeng Liu Ed

  • SKU: BELL-35849758
Tensors For Data Processing Theory Methods And Applications 1st Edition Yipeng Liu Ed
$ 31.00 $ 45.00 (-31%)

5.0

90 reviews

Tensors For Data Processing Theory Methods And Applications 1st Edition Yipeng Liu Ed instant download after payment.

Publisher: Academic Press
File Extension: PDF
File size: 17.85 MB
Pages: 598
Author: Yipeng Liu (ed.)
ISBN: 9780128244470, 012824447X
Language: English
Year: 2021
Edition: 1

Product desciption

Tensors For Data Processing Theory Methods And Applications 1st Edition Yipeng Liu Ed by Yipeng Liu (ed.) 9780128244470, 012824447X instant download after payment.

Tensors for Data Processing: Theory, Methods and Applications presents both classical and state-of-the-art methods on tensor computation for data processing, covering computation theories, processing methods, computing and engineering applications, with an emphasis on techniques for data processing. This reference is ideal for students, researchers and industry developers who want to understand and use tensor-based data processing theories and methods. As a higher-order generalization of a matrix, tensor-based processing can avoid multi-linear data structure loss that occurs in classical matrix-based data processing methods. This move from matrix to tensors is beneficial for many diverse application areas, including signal processing, computer science, acoustics, neuroscience, communication, medical engineering, seismology, psychometric, chemometrics, biometric, quantum physics and quantum chemistry. Provides a complete reference on classical and state-of-the-art tensor-based methods for data processing Includes a wide range of applications from different disciplines Gives guidance for their application

Related Products