Signal reconstruction in sensor arrays using sparse representations $ Dmitri
نویسنده
چکیده
We propose a technique of multisensor signal reconstruction based on the assumption, that source signals are spatially sparse, as well as have sparse representation in a chosen dictionary in time domain. This leads to a large scale convex optimization problem, which involves combined l1-l2 norm minimization. The optimization is carried by the truncated Newton method, using preconditioned conjugate gradients in inner iterations. The byproduct of reconstruction is the estimation of source locations. r 2005 Published by Elsevier B.V.
منابع مشابه
Signal reconstruction in sensor arrays using sparse representations
We propose a technique of multisensor signal reconstruction based on the assumption, that source signals are spatially sparse, as well as have sparse representation in a chosen dictionary in time domain. This leads to a large scale convex optimization problem, which involves combined l1-l2 norm minimization. The optimization is carried by the truncated Newton method, using preconditioned conjug...
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