| Abstract: |
| Expanders play an important role in binary sensors, network measurement, and distributed storage, etc. Via expanders measurements, we propose the expander normalized heavy ball hard thresholding algorithm (ENHB-HT) based on the expander iterative hard thresholding (E-IHT) algorithm. We provide a convergence analysis of ENHB-HT, and it turns out that ENHB-HT can recover an s-sparse signal if the binary sparse measurement matrix A satisfies some mild conditions. Numerical experiments are simulated to support our two main theorems which describe the convergence rate and the accuracy of the proposed algorithm. Simulations are also performed to compare the performance of ENHB-HT and several existing algorithms under different types of noise, the empirical results demonstrate that our algorithm outperforms a few existing ones in the presence of outliers. |
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