FREE delivery to all EXCLUSIVE BOOKS stores nationwide. FREE delivery to your door on all orders over R450. Excludes all international deliveries.

From Algebraic Structures to Tensors

Gérard Favier
    Product form
      FORMAT: Hardback
      YOU COULD EARN 0 FUTURE RETAIL DISCOUNTS.

      This product is either out of print or out of stock. Add it to your wishlist and we will automatically let you know if it comes back into stock. Add to Wishlist

      ESTIMATED DELIVERY: Possibly out of print
      BUY NOW PAY LATER
      From R 0.00 per month!
      3x monthly payments of R 0.00 with
      4x fortnightly payments of R 0.00 with

      This product is either out of print or out of stock. Add it to your wishlist and we will automatically let you know if it comes back into stock. Add to Wishlist

      Nowadays, tensors play a central role for the representation, mining, analysis, and fusion of multidimensional, multimodal, and heterogeneous big data in numerous fields. This set on Matrices and Tensors in Signal Processing aims at giving a self-contained and comprehensive presentation of various concepts and methods, starting from fundamental algebraic structures to advanced tensor-based applications, including recently developed tensor models and efficient algorithms for dimensionality reduction and parameter estimation. Although its title suggests an orientation towards signal processing, the results presented in this set will also be of use to readers interested in other disciplines. This first book provides an introduction to matrices and tensors of higher-order based on the structures of vector space and tensor space. Some standard algebraic structures are first described, with a focus on the hilbertian approach for signal representation, and function approximation based on Fourier series and orthogonal polynomial series. Matrices and hypermatrices associated with linear, bilinear and multilinear maps are more particularly studied. Some basic results are presented for block matrices. The notions of decomposition, rank, eigenvalue, singular value, and unfolding of a tensor are introduced, by emphasizing similarities and differences between matrices and tensors of higher-order.
      Format: Hardback CONTRIBUTORS: Gérard Favier EAN: 9781786301543 COUNTRY: United Kingdom PAGES: WEIGHT: 635 g HEIGHT: 236 cm
      PUBLISHED BY: ISTE Ltd and John Wiley & Sons Inc DATE PUBLISHED: 2019-10-25 CITY: GENRE: TECHNOLOGY & ENGINEERING / Signals & Signal Processing WIDTH: 160 cm SPINE:

      Book Themes:

      Digital signal processing (DSP)

      Customer Reviews

      Be the first to write a review
      0%
      (0)
      0%
      (0)
      0%
      (0)
      0%
      (0)
      0%
      (0)
      Gérard Favier is currently Emeritus Research Director at CNRS and I3S Laboratory, in Sophia Antipolis, France. His research interests include nonlinear system modeling and identification, signal processing applications, tensor models with associated algorithms for big data processing, and tensor approaches for MIMO communication systems.
      Nowadays, tensors play a central role for the representation, mining, analysis, and fusion of multidimensional, multimodal, and heterogeneous big data in numerous fields. This set on Matrices and Tensors in Signal Processing aims at giving a self-contained and comprehensive presentation of various concepts and methods, starting from fundamental algebraic structures to advanced tensor-based applications, including recently developed tensor models and efficient algorithms for dimensionality reduction and parameter estimation. Although its title suggests an orientation towards signal processing, the results presented in this set will also be of use to readers interested in other disciplines. This first book provides an introduction to matrices and tensors of higher-order based on the structures of vector space and tensor space. Some standard algebraic structures are first described, with a focus on the hilbertian approach for signal representation, and function approximation based on Fourier series and orthogonal polynomial series. Matrices and hypermatrices associated with linear, bilinear and multilinear maps are more particularly studied. Some basic results are presented for block matrices. The notions of decomposition, rank, eigenvalue, singular value, and unfolding of a tensor are introduced, by emphasizing similarities and differences between matrices and tensors of higher-order.
      Format: Hardback CONTRIBUTORS: Gérard Favier EAN: 9781786301543 COUNTRY: United Kingdom PAGES: WEIGHT: 635 g HEIGHT: 236 cm
      PUBLISHED BY: ISTE Ltd and John Wiley & Sons Inc DATE PUBLISHED: 2019-10-25 CITY: GENRE: TECHNOLOGY & ENGINEERING / Signals & Signal Processing WIDTH: 160 cm SPINE:

      Book Themes:

      Digital signal processing (DSP)

      Customer Reviews

      Be the first to write a review
      0%
      (0)
      0%
      (0)
      0%
      (0)
      0%
      (0)
      0%
      (0)
      Gérard Favier is currently Emeritus Research Director at CNRS and I3S Laboratory, in Sophia Antipolis, France. His research interests include nonlinear system modeling and identification, signal processing applications, tensor models with associated algorithms for big data processing, and tensor approaches for MIMO communication systems.

      Recently viewed products

      Login

      Forgot your password?

      Don't have an account yet?
      Create account