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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...
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...
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...
In this paper we present an approach for signal denoising using compressive sensing (CS) reconstruction algorithm. It has been known that the successful reconstruction of CS signals can be achieved using threshold based algorithm in the Fourier transform domain, based on just a small number of randomly chosen samples. The resulting signal has higher SNR compared to the input signal, which is used...
This paper presents modification of the TwIST algorithm for Compressive Sensing MRI images reconstruction. Compressive Sensing is new approach in signal processing whose basic idea is recovering signal form small set of available samples. The application of the Compressive Sensing in biomedical imaging has found great importance. It allows significant lowering of the acquisition time, and therefore,...
A task of time delay estimation for wideband signals in non-Gaussian environment is considered. An approach based on application of robust DFT for obtaining spectrum estimates of sensor signals for observation interval is proposed and shown to perform better than conventional approaches for noise modeled as symmetric α-stable process.
Besides revealing useful information, like gender, age, existing impairments, the gait of every person is acknowledged to be so distinctive to allow the personal identification and it is regarded as a valid biometric authentication, similarly to fingerprinting and face recognition. Although the first analyses on the gait were conducted in laboratories with dedicated equipment, portable sensors have...
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