Asymptotic Achievability of the CramÉr–Rao Bound for Noisy Compressive Sampling
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چکیده
منابع مشابه
Comment on "Asymptotic Achievability of the Cramér-Rao Bound for Noisy Compressive Sampling"
In [1], we proved the asymptotic achievability of the Cramér-Rao bound in the compressive sensing setting in the linear sparsity regime. In the proof, we used an erroneous closed-form expression of ασ for the genie-aided Cramér-Rao bound σTr(AIAI) −1 from Lemma 3.5, which appears in Eqs. (20) and (29). The proof, however, holds if one avoids replacing σTr(AIAI) −1 by the expression of Lemma 3.5...
متن کاملCorrections to "Asymptotic Achievability of the Cramér-Rao Bound for Noisy Compressive Sampling"
We consider a model of the form , where is sparse with at most nonzero coefficients in unknown locations, is the observation vector, is the measurement matrix and is the Gaussian noise. We develop a Cramér–Rao bound on the mean squared estimation error of the nonzero elements of , corresponding to the genie-aided estimator (GAE) which is provided with the locations of the nonzero elements of . ...
متن کاملAsymptotic Achievability of the Cramér–Rao Bound For Noisy Compressive Sampling
We consider a model of the form , where is sparse with at most nonzero coefficients in unknown locations, is the observation vector, is the measurement matrix and is the Gaussian noise. We develop a Cramér–Rao bound on the mean squared estimation error of the nonzero elements of , corresponding to the genie-aided estimator (GAE) which is provided with the locations of the nonzero elements of . ...
متن کاملOn the Achievability of Cramér-Rao Bound In Noisy Compressed Sensing
Recently, it has been proved in [1] that in noisy compressed sensing, a joint typical estimator can asymptotically achieve the CramérRao lower bound of the problem. To prove this result, [1] used a lemma, which is provided in [2], that comprises the main building block of the proof. This lemma is based on the assumption of Gaussianity of the measurement matrix and its randomness in the domain o...
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This paper proposes an algorithm for spread spectrum watermark design under compressive sampling (CS) attack using hybridization of genetic algorithm (GA) and neural network. In watermarking application, CS may be viewed as a typical fading-like attack operation on the watermarked image. GA is used to determine the watermark strength taking into consideration of both robustness and imperceptibi...
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ژورنال
عنوان ژورنال: IEEE Transactions on Signal Processing
سال: 2009
ISSN: 1053-587X,1941-0476
DOI: 10.1109/tsp.2008.2010379