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Online coordinate descent for adaptive estimation of sparse signals

Online coordinate descent for adaptive estimation of sparse signals,10.1109/SSP.2009.5278561,Daniele Angelosante,Juan Andres Bazerque,Georgios B. Gian

Online coordinate descent for adaptive estimation of sparse signals   (Citations: 4)
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Two low-complexity sparsity-aware recursive schemes are developed for real-time adaptive signal processing. Both rely on a novel online coordinate descent algorithm which minimizes a time-weighted least-squares cost penalized with the scaled lscr1 norm of the unknown parameters. In addition to computational savings offered when processing time-invariant sparse parameter vectors, both schemes can be used for tracking slowly varying sparse signals. Analysis and preliminary simulations confirm that when the true signal is sparse the proposed estimators converge to a time-weighted least-absolute shrinkage and selection operator, and both outperform sparsity-agnostic recursive least-squares alternatives.
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    • ...To obtain an efficient tracker that can solve a sparse regression problem based on sequentially acquired observations, the recently developed online coordinate descent (OCD) Lasso algorithm [17] is adapted here to the time-varying spectrum sensing problem at hand...
    • ...To track PU activities centrally at the FC, one can employ the adaptive Lasso algorithm of [17] that is termed online coordinate descent (OCD)-Lasso...
    • ...FC, the forgetting factor was used, and weighting factor for the -penalty term was set as suggested in [17] to...

    Seung-Jun Kimet al. Cooperative Spectrum Sensing for Cognitive Radios Using Kriged Kalman ...

    • ...To avoid the computational burden involved, several methods have been developed [8], [9]...

    Vassilis Kekatoset al. Sparsity-aware estimation of nonlinear Volterra kernels

    • ...To track PU activities centrally at the FC, one can employ the adaptive Lasso algorithm of [10] that is termed on-line coordinate descent (OCD)-Lasso...
    • ...[10], with t Lasso the iteration index for the OCD-Lasso algorithm...

    Seung-Jun Kimet al. Sparsity-aware cooperative cognitive radio sensing using channel gain ...

    • ...In order to track the time-varying PU activities, the timeweighted non-negative Lasso formulation adapted from [10] is considered:...
    • ...In [10], a recursive Lasso algorithm, termed on-line coordinate descent (OCD)-Lasso algorithm, was proposed, which performs cyclic iterative minimization of the time-weighted Lasso cost with respect to one entry of p per iteration in the spirit of [11]...

    Seung-Jun Kimet al. Spectrum sensing for cognitive radios using Kriged Kalman filtering

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