Title :
Generalized thresholding sparsity-aware algorithm for low complexity online learning
Author :
Kopsinis, Yannis ; Slavakis, Konstantinos ; Theodoridis, Sergios ; McLaughlin, Steve
Author_Institution :
Univ. of Granada, Granada, Spain
Abstract :
In this paper, a novel scheme for online, sparsity-aware learning is presented. A new theory is developed that allows for the incorporation, in a unifying way, of different thresholding rules to promote sparsity, that may even be of a nonconvex nature. The complexity of the algorithm exhibits a linear dependence on the number of free parameters.
Keywords :
adaptive filters; learning (artificial intelligence); adaptive filtering; low complexity online learning; sparsity-aware algorithm; sparsity-aware learning; thresholding operator; Computational complexity; Convergence; Noise; Noise measurement; Training; Vectors; Adaptive filtering; signal recovery; sparsity; thresholding operators;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
Conference_Location :
Kyoto
Print_ISBN :
978-1-4673-0045-2
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2012.6288615
