Finding Zeros: Greedy Detection of Holes
classification
💻 cs.IT
math.IT
keywords
algorithmsdetectioncoherenceempiricalperformancealgorithmalongassumes
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In this paper, motivated by the setting of white-space detection [1], we present theoretical and empirical results for detection of the zero-support E of x \in Cp (xi = 0 for i \in E) with reduced-dimension linear measurements. We propose two low- complexity algorithms based on one-step thresholding [2] for this purpose. The second algorithm is a variant of the first that further assumes the presence of group-structure in the target signal [3] x. Performance guarantees for both algorithms based on the worst- case and average coherence (group coherence) of the measurement matrix is presented along with the empirical performance of the algorithms.
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