Abstract
The iterative hard-threshold algorithm has recently been proposed to handle sparse regularisation problems arising in compressed sensing and other sparse signal processing problems. The algorithm is attractive owing to its simplicity; however, it converges slowly. An accelerated algorithm of this iterative method is proposed based on momentum and adaptive learning rate. Experiments with the sparse signal reconstruction show the effectiveness of the proposed algorithm.
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