A New Smoothed L0 Regularization Approach for Sparse Signal Recovery

<figure class="figure-group responsive"><div class="sub-figure" id="a"><object data="https://static.hindawi.com/articles/mpe/volume-2019/1978154/figures/1978154.fig.002a.svgz" name="1978154.fig.002a" type="image/svg+xml"></object><div class="fig-label"><b>(a) </b>RSR of recovery signal</div></div><div class="sub-figure" id="b"><object data="https://static.hindawi.com/articles/mpe/volume-2019/1978154/figures/1978154.fig.002b.svgz" name="1978154.fig.002b" type="image/svg+xml"></object><div class="fig-label"><b>(b) </b>NMSE of recovery signal</div></div></figure>

<p>Signal recovery in noiseless case. RSR and NMSE of recovery signal are displayed at intervals of 5 with sparsity from 1 to 61. The comparison algorithms are BPDN, SL0, L2-SL0, Lp-RLS, and RRSL0. The experimental results were obtained by 100 independent repeated experiments.</p>

Mathematical Problems in Engineering

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Figure 2: A New Smoothed L0 Regularization Approach for Sparse Signal Recovery 