Matrix and Tensor Decompositions in Signal Processing, Volume 2 / Edition 1

by Gérard Favier

Overview

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.

Product Details

ISBN-13:	9781786301550
Publisher:	Wiley
Publication date:	08/31/2021
Pages:	384
Product dimensions:	0.39(w) x 0.39(h) x 0.39(d)

About the Author

FAVIER Gérard, Emeritus Research Director at CNRS.

Table of Contents

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)