A sample-complexity bound for l1-TV compressed sensing is derived, and an unrolled proximal-gradient solver (LPGM-ISTA) recovers ECG signals with better accuracy and speed than standard iterative methods.
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Theory and Fast Learned Solver for $\ell^1$-TV Regularization
A sample-complexity bound for l1-TV compressed sensing is derived, and an unrolled proximal-gradient solver (LPGM-ISTA) recovers ECG signals with better accuracy and speed than standard iterative methods.