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- W2003285291 abstract "The classical Compressive Sensing (CS) techniques for wideband spectral sensing consist of a two-stage estimation detection approach. A novel approach is proposed to solve the detection problem directly from observations with incomplete frequency information, for e.g., signals acquired using sub-Nyquist rate sampling. The wideband occupancy detection problem is formulated as a multiple hypothesis testing problem under a non-Bayesian framework, and a Neyman-Pearson-like criterion is proposed. The detector based on exhaustive search performs better than the conventional CS based techniques. However, it is impractical for large block sizes. Hence, we propose a sub-optimal greedy algorithm whose complexity and performance can be traded-off by construction." @default.
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- W2003285291 date "2012-06-01" @default.
- W2003285291 modified "2023-10-14" @default.
- W2003285291 title "Multiple hypothesis testing for compressive wideband sensing" @default.
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- W2003285291 doi "https://doi.org/10.1109/spawc.2012.6292978" @default.
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