이진 희소 신호의 L₀ 복원 성능에 대한 상한치

Upper Bound for L₀ Recovery Performance of Binary Sparse Signals

In this paper, we consider a binary recovery framework of the Compressed Sensing (CS) problem. We derive an upper bound for $L_0$ recovery performance of a binary sparse signal in terms of the dimension N and sparsity K of signals, the number of measurements M. We show that the upper bound obtained from this work goes to the limit bound when the sensing matrix sufficiently become dense. In addition, for perfect recovery performance, if the signals are very sparse, the sensing matrices required for $L_0$ recovery are little more dense.