Matrix and Tensor Decompositions in Signal Processing, Volume 2

Gérard Favier (CNRS)

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English

ISTE Ltd and John Wiley & Sons Inc
10 August 2021

Electronics & communications engineering; 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 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.

By: Gérard Favier (CNRS)
Imprint: ISTE Ltd and John Wiley & Sons Inc
Country of Publication: United Kingdom
Edition: Volume 2
Dimensions: Height: 10mm, Width: 10mm,
Weight: 454g
ISBN: 9781786301550
ISBN 10: 1786301555
Pages: 384
Publication Date: 10 August 2021
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

Volume 2 1. Matrix decompositions 2. Tensor decompositions 3. Tensor networks 4. Parametric estimation of tensor decompositions 5. Recovery of low rank matrix reconnects (LRMR) and low-tensor recovery (LRTR)

FAVIER Gérard, Emeritus Research Director at CNRS.