iterativeshrinkage/thresholdingalgorithms (ISTAs) have recently been proposed to solve linear inverse problems arising in signal and image processing. The convergence rate of ISTAs relies on a scalar known as st...
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iterativeshrinkage/thresholdingalgorithms (ISTAs) have recently been proposed to solve linear inverse problems arising in signal and image processing. The convergence rate of ISTAs relies on a scalar known as step size, which is unknown and expensive to compute in practice especially for large-scale problems. Usually a backtracking rule is employed to choose an appropriate step size which guarantees the convergence condition and speed up ISTAs at the same time. In this paper, we propose a new method to compute the step size exactly. Experimental results show the effectiveness of the proposed algorithm.
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