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ICONIP
2008
15 years 1 months ago
Improved Sparse Bump Modeling for Electrophysiological Data
Bump modeling is a method used to extract oscillatory bursts in electrophysiological signals, who are most likely to be representative of local synchronies. In this paper we presen...
François B. Vialatte, Justin Dauwels, Jordi...
MFCS
2010
Springer
14 years 10 months ago
Evaluating Non-square Sparse Bilinear Forms on Multiple Vector Pairs in the I/O-Model
We consider evaluating one bilinear form defined by a sparse Ny × Nx matrix A having h entries on w pairs of vectors The model of computation is the semiring I/O-model with main ...
Gero Greiner, Riko Jacob
ICIP
2010
IEEE
14 years 9 months ago
Image modeling and enhancement via structured sparse model selection
An image representation framework based on structured sparse model selection is introduced in this work. The corresponding modeling dictionary is comprised of a family of learned ...
Guoshen Yu, Guillermo Sapiro, Stéphane Mall...
SIAMNUM
2011
139views more  SIAMNUM 2011»
14 years 6 months ago
Adaptive Wavelet Schemes for Parabolic Problems: Sparse Matrices and Numerical Results
A simultaneous space-time variational formulation of a parabolic evolution problem is solved with an adaptive wavelet method. This method is shown to converge with the best possibl...
Nabi Chegini, Rob Stevenson
ICASSP
2011
IEEE
14 years 3 months ago
Estimation and dynamic updating of time-varying signals with sparse variations
This paper presents an algorithm for an 1-regularized Kalman filter. Given observations of a discrete-time linear dynamical system with sparse errors in the state evolution, we e...
Muhammad Salman Asif, Adam Charles, Justin K. Romb...