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This paper analyzes the performance of different compressive sensing algorithms applied to signals with polynomial and cosine modulated phases, that usually appear in radar communications. In order to provide sparsity in the Fourier transform domain, the signal components are firstly demodulated by a direct parameter search method. In this way, the signals are sparsified in the DFT domain. The performance...
A hardware architecture for the single iteration algorithm is proposed in this paper. Single iteration algorithm enables reconstruction of the full signal when small number of signal samples is available. The algorithm is based on the threshold calculation, and allows distinguishing between signal components and noise that appears as a consequence of missing samples. The proposed system for hardware...
The application of Compressive sensing approach to the speech and musical signals is considered in this paper. Compressive sensing (CS) is a new approach to the signal sampling that allows signal reconstruction from a small set of randomly acquired samples. This method is developed for the signals that exhibit the sparsity in a certain domain. Here we have observed two sparsity domains: discrete Fourier...
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