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A Fast Algorithm for Recovery of Jointly Sparse Vectors based on the Alternating Direction Methods

Published on May 06, 20113850 Views

The standard compressive sensing (CS) aims to recover sparse signal from single measurement vector which is known as SMV model. By contrast, recovery of sparse signals from multiple measurement vector

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A Fast Algorithm for Recovery of Jointly Sparse Vectors based on the Alternating Direction Methods00:00
The author (Hongtao Lu)00:10
Shanghai Jiao Tong University00:23
Outline00:43
Introduction (1)00:59
Introduction (2)01:17
Introduction (3)01:55
Introduction (4)02:19
Introduction (5)02:28
Problem formulation02:59
Problem formulation (1)03:05
Problem formulation (2)03:21
Problem formulation (3)03:25
Problem formulation (4)03:36
Existing methods04:02
Existing methods (1)04:04
Existing methods (2)04:19
Existing methods (3)04:46
Our Algorithm (MMV-ADM)04:59
Our Algorithm (1)05:07
Our Algorithm (2)05:38
Our Algorithm (3)06:15
Our Algorithm (4)06:37
Our Algorithm (5)07:11
Our Algorithm (6)07:19
Our Algorithm (7)08:06
Our Algorithm (8)08:37
Our Algorithm (9)08:44
Our Algorithm (10)08:47
Our Algorithm (11)08:54
Experiments09:01
Experiments (1)09:05
Experiments (2)09:40
Experiments (3)10:20
Experiments (4)10:30
Experiments (5)10:35
Experiments (6)10:44
Conclusion and future works10:59
Conclusion11:01
Future Works11:25