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TSP
2010
13 years 3 months ago
Variance-component based sparse signal reconstruction and model selection
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Kun Qiu, Aleksandar Dogandzic
TSP
2010
13 years 3 months ago
Noninvertible gabor transforms
Abstract--Time-frequency analysis, such as the Gabor transform, plays an important role in many signal processing applications. The redundancy of such representations is often dire...
Ewa Matusiak, Tomer Michaeli, Yonina C. Eldar
TSP
2010
13 years 3 months ago
Distributed sparse linear regression
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....
Gonzalo Mateos, Juan Andrés Bazerque, Georg...
TSP
2010
13 years 3 months ago
Optimization and analysis of distributed averaging with short node memory
Distributed averaging describes a class of network algorithms for the decentralized computation of aggregate statistics. Initially, each node has a scalar data value, and the goal...
Boris N. Oreshkin, Mark Coates, Michael G. Rabbat
TSP
2010
13 years 3 months ago
Noisy data and impulse response estimation
Abstract--This paper investigates the impulse response estimation of linear time-invariant (LTI) systems when only noisy finitelength input-output data of the system is available. ...
Soosan Beheshti, Munther A. Dahleh
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