Search preferences
Skip to main search results

Search filters

Product Type

  • All Product Types 
  • Books (1)
  • Magazines & Periodicals (No further results match this refinement)
  • Comics (No further results match this refinement)
  • Sheet Music (No further results match this refinement)
  • Art, Prints & Posters (No further results match this refinement)
  • Photographs (No further results match this refinement)
  • Maps (No further results match this refinement)
  • Manuscripts & Paper Collectibles (No further results match this refinement)

Condition Learn more

  • New (1)
  • As New, Fine or Near Fine (No further results match this refinement)
  • Very Good or Good (No further results match this refinement)
  • Fair or Poor (No further results match this refinement)
  • As Described (No further results match this refinement)

Binding

Collectible Attributes

Language (1)

Price

  • Any Price 
  • Under £ 20 (No further results match this refinement)
  • £ 20 to £ 35 (No further results match this refinement)
  • Over £ 35 
Custom price range (£)

Free Shipping

  • Free Shipping to U.S.A. (No further results match this refinement)

Seller Location

  • Yipeng (Associate Professor Liu

    Language: English

    Published by Elsevier Science Publishing Co Inc Okt 2021, 2021

    ISBN 10: 012824447X ISBN 13: 9780128244470

    Seller: AHA-BUCH GmbH, Einbeck, Germany

    Seller rating 5 out of 5 stars 5-star rating, Learn more about seller ratings

    Contact seller

    £ 176.19

    £ 57.41 shipping
    Ships from Germany to U.S.A.

    Quantity: 1 available

    Add to basket

    Taschenbuch. Condition: Neu. Neuware - 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.