Cover Image
Read Now

Matrix and tensor decompositions in signal processing

The second volume will deal with a presentation of the main matrix and tensor decompositions and their properties of uniqueness, as well as very useful tensor networks for the analysis of massive data. Parametric estimation algorithms will be presented for the identification of the main tensor decom...

Full description

Bibliographic Details
Main Author: Favier, Gérard
Format: eBook
Language:English
Published: London ISTE, Ltd. 2021
Subjects:
Matrices / Http://id.loc.gov/authorities/subjects/sh85082210
Matrices
Computer Algorithms / Fast
Algorithms / Fast
Matrices / Fast
Computer Algorithms / Http://id.loc.gov/authorities/subjects/sh91000149
Algorithms / Http://id.loc.gov/authorities/subjects/sh85003487
Traitement Du Signal / Techniques Numériques / Mathématiques
Algorithmes
Calculus Of Tensors / Http://id.loc.gov/authorities/subjects/sh85018808
Signal Processing / Digital Techniques / Mathematics / Fast
Algorithms / Aat
Calculus Of Tensors / Fast
Calcul Tensoriel
Signal Processing / Digital Techniques / Mathematics / Http://id.loc.gov/authorities/subjects/sh94001318
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Description
Summary:The second volume will deal with a presentation of the main matrix and tensor decompositions and their properties of uniqueness, as well as very useful tensor networks for the analysis of massive data. Parametric estimation algorithms will be presented for the identification of the main tensor decompositions. After a brief historical review of the compressed sampling methods, an overview of the main methods of retrieving matrices and tensors with missing data will be performed under the low rank hypothesis. Illustrative examples will be provided
Physical Description:1 volume illustrations
ISBN:9781119700999

Similar Items