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JACM
2011
152views more  JACM 2011»
13 years 21 days ago
Robust principal component analysis?
This paper is about a curious phenomenon. Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Can we recover each component i...
Emmanuel J. Candès, Xiaodong Li, Yi Ma, Joh...
TASLP
2010
118views more  TASLP 2010»
13 years 8 months ago
Time-Frequency Sparsity by Removing Perceptually Irrelevant Components Using a Simple Model of Simultaneous Masking
Abstract—We present an algorithm for removing timefrequency components, found by a standard Gabor transform, of a “real-world” sound while causing no audible difference to th...
Péter Balázs, Bernhard Laback, Gerha...
ICSE
2011
IEEE-ACM
13 years 1 months ago
Predictable dynamic deployment of components in embedded systems
—Dynamic reconfiguration – the ability to hot swap a component, or to introduce a new component into the system – is essential to supporting evolutionary change in long-live ...
Ana Petricic
NN
2000
Springer
159views Neural Networks» more  NN 2000»
13 years 9 months ago
Independent component analysis for noisy data -- MEG data analysis
ICA (independent component analysis) is a new, simple and powerful idea for analyzing multi-variant data. One of the successful applications is neurobiological data analysis such ...
Shiro Ikeda, Keisuke Toyama
PC
2010
177views Management» more  PC 2010»
13 years 8 months ago
Parallel graph component labelling with GPUs and CUDA
Graph component labelling, which is a subset of the general graph colouring problem, is a computationally expensive operation that is of importance in many applications and simula...
Kenneth A. Hawick, Arno Leist, Daniel P. Playne