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The paper examines an application of the gradient-based algorithm to image denoising with noise values being in the range of the available (non-noisy) pixel values. The analyzed image is considered to be sparse in the 2D-DCT domain. The presented algorithm is a generalization of the previous results on denoising images when the noisy pixels can be detected and eliminated using the L-statistics. The...
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...
An analysis of signal reconstruction possibility using a small set of samples corrupted by noise is considered. False detection and/or misdetection of sparse signal components may occur as a twofold influence of noise: one is a consequence of missing samples, while the other appears from an external source. This analysis allows us to determine a minimal number of available samples required for a non-iterative...
This paper deals with signal characterization in communication systems. An algorithm for components separation of highly multicomponent wireless signals has been described. Eigenvalue decomposition method along with time-frequency signal distribution is used. Approach has been tested on synthetic IEEE 802.11b wireless signal. This method can be useful for the elimination of frequency collisions -...
An approach to multiwindow time-frequency analysis that provides robust performance in noisy environment is proposed. The concept of robust estimates of instantaneous frequency is used to define the optimal weighting coefficients for the multiwindow spectrogram. The proposed form of multiwindow spectrogram provides improved instantaneous frequency estimation for nonstationary signals in the presence...
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