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Dictionary learning for sparse representation has been an ac-tive topic in the field of image proces...
Dictionary learning problem has become an active topic for decades. Most existing learning methods t...
Recent years have witnessed a growing interest in the sparse representation problem. Prior work demo...
This article deals with learning dictionaries for sparse approximation whose atoms are both adapted ...
This work was supported by the Queen Mary University of London School Studentship, the EU FET-Open p...
© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
PhDOver-complete transforms have recently become the focus of a wide wealth of research in signal p...
Assuming that a set of source signals is sparsely representable in a given dictionary, we show how t...
International audienceShift-invariant dictionaries are generated by taking all the possible shifts o...
Recordings of audio often show undesirable alterations, mostly the presence of noise or the corrupti...
During the past decade, sparse representation has attracted much attention in the signal processing ...
In the sparse representation model, the design of overcomplete dictionaries plays a key role for the...
Sparse dictionary learning has attracted enormous interest in image processing and data representati...
Optimizing the mutual coherence of a learned dictionary plays an important role in sparse representa...
Dictionary learning for sparse representation has been an ac-tive topic in the field of image proces...
Dictionary learning problem has become an active topic for decades. Most existing learning methods t...
Recent years have witnessed a growing interest in the sparse representation problem. Prior work demo...
This article deals with learning dictionaries for sparse approximation whose atoms are both adapted ...
This work was supported by the Queen Mary University of London School Studentship, the EU FET-Open p...
© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
PhDOver-complete transforms have recently become the focus of a wide wealth of research in signal p...
Assuming that a set of source signals is sparsely representable in a given dictionary, we show how t...
International audienceShift-invariant dictionaries are generated by taking all the possible shifts o...
Recordings of audio often show undesirable alterations, mostly the presence of noise or the corrupti...
During the past decade, sparse representation has attracted much attention in the signal processing ...
In the sparse representation model, the design of overcomplete dictionaries plays a key role for the...
Sparse dictionary learning has attracted enormous interest in image processing and data representati...
Optimizing the mutual coherence of a learned dictionary plays an important role in sparse representa...
Dictionary learning for sparse representation has been an ac-tive topic in the field of image proces...
Dictionary learning problem has become an active topic for decades. Most existing learning methods t...
Recent years have witnessed a growing interest in the sparse representation problem. Prior work demo...