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ICASSP
2011
IEEE
13 years 25 days ago
Multi-channel EEG compression based on matrix and tensor decompositions
Compression schemes for EEG signals are developed based on matrix and tensor decomposition. Various ways to arrange EEG signals into matrices and tensors are explored, and several...
Justin Dauwels, K. Srinivasan, M. Ramasubba Reddy,...
DCC
2010
IEEE
14 years 4 months ago
On the Systematic Measurement Matrix for Compressed Sensing in the Presence of Gross Errors
Inspired by syndrome source coding using linear error-correcting codes, we explore a new form of measurement matrix for compressed sensing. The proposed matrix is constructed in t...
Zhi Li, Feng Wu, John Wright
SCALESPACE
2009
Springer
14 years 3 months ago
PDE-Driven Adaptive Morphology for Matrix Fields
Matrix fields are important in many applications since they are the adequate means to describe anisotropic behaviour in image processing models and physical measurements. A promin...
Bernhard Burgeth, Michael Breuß, Luis Pizarr...
CVPR
2008
IEEE
14 years 3 months ago
Unified Principal Component Analysis with generalized Covariance Matrix for face recognition
Recently, 2DPCA and its variants have attracted much attention in face recognition area. In this paper, some efforts are made to discover the underlying fundaments of these method...
Shiguang Shan, Bo Cao, Yu Su, Laiyun Qing, Xilin C...
ICPP
2008
IEEE
14 years 3 months ago
Improving the Performance of Multithreaded Sparse Matrix-Vector Multiplication Using Index and Value Compression
Abstract—The Sparse Matrix-Vector Multiplication kernel exhibits limited potential for taking advantage of modern shared memory architectures due to its large memory bandwidth re...
Kornilios Kourtis, Georgios I. Goumas, Nectarios K...