L0-Optimization for Channel and DOA Sparse Estimation

Sorted L1/L2 Minimization for Sparse Signal Recovery

Wang, Chao
Yan, Ming
Yu, Junjie

August 2023

This paper introduces a novel approach for recovering sparse signals using sorted L1/L2 minimization...

Subspace Based Blind Sparse Channel Estimation

Hayashi, Kazunori
Matsushima, Hiroki
Sakai, Hideaki
De Carvalho, Elisabeth
Popovski, Petar

January 2012

The paper proposes a subspace based blind sparse channel estimation method using 1–2 optimization by...

Estimation of sparse distributions

Hyder, Md. Mashud

January 2012

Research Doctorate - Doctor of Philosophy (PhD)A vector is called sparse when most of its components...

L0-Optimization for Channel and DOA Sparse Estimation

Chinatto, Adilson
Soubies, Emmanuel
Junqueira, Cynthia
Romano, Joâo M. T.
Larzabal, Pascal
Barbot, Jean-Pierre
Blanc-Féraud, Laure

December 2015

International audienceThis paper is devoted to two classical sparse problems in array processing: Ch...

Direction-of-Arrival Estimation through Exact Continuous l20-Norm Relaxation

Soubies, Emmanuel
Chinatto, Adilson
Larzabal, Pascal
Romano, João,
Blanc-Féraud, Laure

January 2021

International audienceOn-grid based direction-of-arrival (DOA) estimation methods rely on the resolu...

Optimization of a Geman-McClure like criterion for sparse signal deconvolution

Castella, Marc
Pesquet, Jean-Christophe

December 2015

International audienceThis paper deals with the problem of recovering a sparse unknown signal from a...

On Recovery of Sparse Signals Via \ell _{1} Minimization

Cai, T. Tony
Xu, Guangwu
Zhang, Jun

July 2009

This paper considers constrained lscr1 minimization methods in a unified framework for the recovery ...

Norm Penalized Joint-Optimization NLMS Algorithms for Broadband Sparse Adaptive Channel Estimation

Yanyan Wang

July 2017

A joint-optimization method is proposed for enhancing the behavior of the l 1 -norm- and sum-...

Sparse Representations & Compressed Sensing with application to the problem of Direction-of-Arrival estimation.

Gretsistas, Aris

June 2013

PhDThe significance of sparse representations has been highlighted in numerous signal processing ap...

Greedy adaptive algorithms for sparse representations

Onose, Alexandru

January 2014

A vector or matrix is said to be sparse if the number of non-zero elements is significantly smaller ...

Smooth Approximation l0-Norm Constrained Affine Projection Algorithm and Its Applications in Sparse Channel Estimation

Yingsong Li
Masanori Hamamura

January 2014

We propose a smooth approximation l0-norm constrained affine projection algorithm (SL0-APA) to impro...

Exact Sparse Approximation Problems via Mixed-Integer Programming: Formulations and Computational Performance

Bourguignon, Sébastien
Ninin, Jordan
Carfantan, Hervé
Mongeau, Marcel

March 2016

International audienceSparse approximation addresses the problem of approximately fitting a linear m...

A greedy algorithm to extract sparsity degree for l1/l0-equivalence in a deterministic context

Pustelnik, Nelly
Dossal, Charles, H
Turcu, Flavius
Berthoumieu, Yannick
Ricoux, Philippe

August 2012

International audienceThis paper investigates the problem of designing a deterministic system matrix...

Mixed-integer programming methods for sparse optimization in signal processing

Ben mhenni, Ramzi

May 2020

L’approximation parcimonieuse consiste à ajuster un modèle de données linéaire au sens des moindres ...

Sorted L1/L2 Minimization for Sparse Signal Recovery

Wang, Chao
Yan, Ming
Yu, Junjie

August 2023

This paper introduces a novel approach for recovering sparse signals using sorted L1/L2 minimization...

Subspace Based Blind Sparse Channel Estimation

Hayashi, Kazunori
Matsushima, Hiroki
Sakai, Hideaki
De Carvalho, Elisabeth
Popovski, Petar

January 2012

The paper proposes a subspace based blind sparse channel estimation method using 1–2 optimization by...

Estimation of sparse distributions

Hyder, Md. Mashud

January 2012

Research Doctorate - Doctor of Philosophy (PhD)A vector is called sparse when most of its components...

L0-Optimization for Channel and DOA Sparse Estimation

Chinatto, Adilson
Soubies, Emmanuel
Junqueira, Cynthia
Romano, Joâo M. T.
Larzabal, Pascal
Barbot, Jean-Pierre
Blanc-Féraud, Laure

December 2015

International audienceThis paper is devoted to two classical sparse problems in array processing: Ch...

Direction-of-Arrival Estimation through Exact Continuous l20-Norm Relaxation

Soubies, Emmanuel
Chinatto, Adilson
Larzabal, Pascal
Romano, João,
Blanc-Féraud, Laure

January 2021

International audienceOn-grid based direction-of-arrival (DOA) estimation methods rely on the resolu...

Optimization of a Geman-McClure like criterion for sparse signal deconvolution

Castella, Marc
Pesquet, Jean-Christophe

December 2015

International audienceThis paper deals with the problem of recovering a sparse unknown signal from a...

On Recovery of Sparse Signals Via \ell _{1} Minimization

Cai, T. Tony
Xu, Guangwu
Zhang, Jun

July 2009

This paper considers constrained lscr1 minimization methods in a unified framework for the recovery ...

Norm Penalized Joint-Optimization NLMS Algorithms for Broadband Sparse Adaptive Channel Estimation

Yanyan Wang

July 2017

A joint-optimization method is proposed for enhancing the behavior of the l 1 -norm- and sum-...

Sparse Representations & Compressed Sensing with application to the problem of Direction-of-Arrival estimation.

Gretsistas, Aris

June 2013

PhDThe significance of sparse representations has been highlighted in numerous signal processing ap...

Greedy adaptive algorithms for sparse representations

Onose, Alexandru

January 2014

A vector or matrix is said to be sparse if the number of non-zero elements is significantly smaller ...

Smooth Approximation l0-Norm Constrained Affine Projection Algorithm and Its Applications in Sparse Channel Estimation

Yingsong Li
Masanori Hamamura

January 2014

We propose a smooth approximation l0-norm constrained affine projection algorithm (SL0-APA) to impro...

Exact Sparse Approximation Problems via Mixed-Integer Programming: Formulations and Computational Performance

Bourguignon, Sébastien
Ninin, Jordan
Carfantan, Hervé
Mongeau, Marcel

March 2016

International audienceSparse approximation addresses the problem of approximately fitting a linear m...

A greedy algorithm to extract sparsity degree for l1/l0-equivalence in a deterministic context

Pustelnik, Nelly
Dossal, Charles, H
Turcu, Flavius
Berthoumieu, Yannick
Ricoux, Philippe

August 2012

International audienceThis paper investigates the problem of designing a deterministic system matrix...

Mixed-integer programming methods for sparse optimization in signal processing

Ben mhenni, Ramzi

May 2020

L’approximation parcimonieuse consiste à ajuster un modèle de données linéaire au sens des moindres ...

Sorted L1/L2 Minimization for Sparse Signal Recovery

Wang, Chao
Yan, Ming
Yu, Junjie

August 2023

This paper introduces a novel approach for recovering sparse signals using sorted L1/L2 minimization...

Subspace Based Blind Sparse Channel Estimation

Hayashi, Kazunori
Matsushima, Hiroki
Sakai, Hideaki
De Carvalho, Elisabeth
Popovski, Petar

January 2012

The paper proposes a subspace based blind sparse channel estimation method using 1–2 optimization by...

Estimation of sparse distributions

Hyder, Md. Mashud

January 2012

Research Doctorate - Doctor of Philosophy (PhD)A vector is called sparse when most of its components...

L0-Optimization for Channel and DOA Sparse Estimation

Abstract

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L0-Optimization for Channel and DOA Sparse Estimation

Abstract

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