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Concise Signal Models (col10635)
Summary: This collection reviews fundamental concepts underlying the use of concise models for signal processing. Topics are presented from a geometric perspective and include low-dimensional linear, sparse, and manifold-based signal models, approximation, compression, dimensionality reduction, and Compressed Sensing.
Subject: Science and Technology
Language: English
Popularity: 73.70%
Revised: 2009-09-14
Revisions: 4
Approximation (m18727)
Summary: This collection reviews fundamental concepts underlying the use of concise models for signal processing. Topics are presented from a geometric perspective and include low-dimensional linear, sparse, and manifold-based signal models, approximation, compression, dimensionality reduction, and Compressed Sensing.
Subject: Science and Technology
Language: English
Popularity: 48.05%
Revised: 2009-09-22
Revisions: 5
Compressed Sensing (m18733)
Summary: This collection reviews fundamental concepts underlying the use of concise models for signal processing. Topics are presented from a geometric perspective and include low-dimensional linear, sparse, and manifold-based signal models, approximation, compression, dimensionality reduction, and Compressed Sensing.
Subject: Science and Technology
Language: English
Popularity: 86.48%
Revised: 2009-09-22
Revisions: 5
Compression (m18729)
Summary: This collection reviews fundamental concepts underlying the use of concise models for signal processing. Topics are presented from a geometric perspective and include low-dimensional linear, sparse, and manifold-based signal models, approximation, compression, dimensionality reduction, and Compressed Sensing.
Subject: Science and Technology
Language: English
Popularity: 36.30%
Revised: 2009-09-22
Revisions: 3
Dimensionality Reduction (m18732)
Summary: This collection reviews fundamental concepts underlying the use of concise models for signal processing. Topics are presented from a geometric perspective and include low-dimensional linear, sparse, and manifold-based signal models, approximation, compression, dimensionality reduction, and Compressed Sensing.
Subject: Science and Technology
Language: English
Popularity: 62.23%
Revised: 2009-09-22
Revisions: 5
Gelfand n-widths (m15133)
Language: English
Popularity: 62.26%
Revised: 2007-09-21
Revisions: New
General Mathematical Preliminaries (m18721)
Summary: This collection reviews fundamental concepts underlying the use of concise models for signal processing. Topics are presented from a geometric perspective and include low-dimensional linear, sparse, and manifold-based signal models, approximation, compression, dimensionality reduction, and Compressed Sensing.
Subject: Science and Technology
Language: English
Popularity: 23.44%
Revised: 2008-12-03
Revisions: 2
Introduction to Concise Signal Models (m18720)
Summary: This collection reviews fundamental concepts underlying the use of concise models for signal processing. Topics are presented from a geometric perspective and include low-dimensional linear, sparse, and manifold-based signal models, approximation, compression, dimensionality reduction, and Compressed Sensing.
Subject: Science and Technology
Language: English
Popularity: 39.79%
Revised: 2009-09-22
Revisions: 5
Low-Dimensional Signal Models (m18726)
Summary: This collection reviews fundamental concepts underlying the use of concise models for signal processing. Topics are presented from a geometric perspective and include low-dimensional linear, sparse, and manifold-based signal models, approximation, compression, dimensionality reduction, and Compressed Sensing.
Subject: Science and Technology
Language: English
Popularity: 49.22%
Revised: 2009-09-22
Revisions: 4
Manifolds (m18722)
Summary: This collection reviews fundamental concepts underlying the use of concise models for signal processing. Topics are presented from a geometric perspective and include low-dimensional linear, sparse, and manifold-based signal models, approximation, compression, dimensionality reduction, and Compressed Sensing.
Subject: Science and Technology
Language: English
Popularity: 47.46%
Revised: 2009-09-22
Revisions: 4
Signal Dictionaries and Representations (m18724)
Summary: This collection reviews fundamental concepts underlying the use of concise models for signal processing. Topics are presented from a geometric perspective and include low-dimensional linear, sparse, and manifold-based signal models, approximation, compression, dimensionality reduction, and Compressed Sensing.
Subject: Science and Technology
Language: English
Popularity: 57.00%
Revised: 2009-09-22
Revisions: 5
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Total Collections: 1317
Total Modules: 21763