A neural network can generate binary sensing matrices with lower mutual coherence than random matrices by optimizing coherence-based losses without any training data.
Compressed sensing using generative models
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Learning the Mathematical Property for Designing Low Mutual Coherence Binary Sensing Matrices
A neural network can generate binary sensing matrices with lower mutual coherence than random matrices by optimizing coherence-based losses without any training data.