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IGARSS
2009
13 years 5 months ago
Unmixing Sparse Hyperspectral Mixtures
Finding an accurate sparse approximation of a spectral vector described by a linear model, when there is available a library of possible constituent signals (called endmembers or ...
Marian-Daniel Iordache, José M. Bioucas-Dia...
CORR
2011
Springer
191views Education» more  CORR 2011»
13 years 2 months ago
A Message-Passing Receiver for BICM-OFDM over Unknown Clustered-Sparse Channels
We propose a factor-graph-based approach to joint channel-estimationand-decoding of bit-interleaved coded orthogonal frequency division multiplexing (BICM-OFDM). In contrast to ex...
Philip Schniter
FOCM
2011
175views more  FOCM 2011»
13 years 2 months ago
Convergence of Fixed-Point Continuation Algorithms for Matrix Rank Minimization
The matrix rank minimization problem has applications in many fields such as system identification, optimal control, low-dimensional embedding etc. As this problem is NP-hard in ...
Donald Goldfarb, Shiqian Ma
MP
2011
13 years 2 months ago
Null space conditions and thresholds for rank minimization
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in machine learning, control theory, and discrete geometry. This c...
Benjamin Recht, Weiyu Xu, Babak Hassibi
SIAMIS
2011
13 years 2 months ago
Gradient-Based Methods for Sparse Recovery
The convergence rate is analyzed for the sparse reconstruction by separable approximation (SpaRSA) algorithm for minimizing a sum f(x) + ψ(x), where f is smooth and ψ is convex, ...
William W. Hager, Dzung T. Phan, Hongchao Zhang