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Fig. 1 | EURASIP Journal on Advances in Signal Processing

Fig. 1

From: Semi-tensor product-based one-bit compressed sensing

Fig. 1

Illustration on random hyperplane tessellation in \({\mathbb{R}}^{2}\). a corresponds to homogeneous hyperplanes in which case any two points on a ray from the origin cannot be separated even if one uses all possible hyperplanes. b Corresponds to hyperplanes with random parallel shifts (resulted by random dithers) in which case we can approximate distances between signals

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