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On cyclic correlation approaches for blind identification of FIR communications channels
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Blind identification and order estimation of FIR communications channels using cyclic statistics
No full textLezioni di Teoria dei Segnali (I modulo)
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Lezioni di Teoria dei Segnali (II modulo)
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Non-Minimum Phase AR Identification Using Blind Deconvolution Methods
No full textPublication in the conference proceedings of EUSIPCO, Rhodes, Greece, 199
Hierarchical image analysis using Radon Transform: an application to error concealment
No full textIn this contribution, we show how a hierarchical edge image analysis at macroblock, block and subblock levels allows identifying prominent directional image components. The analysis, performed in the Radon domain, selects the scale level at which the image features present a directional structure that can be better reconstructed by a directional spatial interpolation. When the directional information is known at the decoder side it can drive the spatial error concealment. The experimental results, referring to the case of H.264 coded video, show the significant improvement of the decoded video visual quality achievable by the described technique. © 2005 IEEE
Gain Control Free Blind Frequency Offset Estimator for General QAM Communication
No full textIn this paper we present a novel not data aided gain control free frequency offset estimator for general Quadrature Amplitude Modulated constellations along with its theoretical performance analysis. The estimator is based on applying a tentative frequency offset compensation by means of a nonlinear transformation of the received signal samples and on estimating an accumulation function in different angular windows. For perfect frequency offset compensation, the measurements are suitably clustered and their accumulation, named \Constellation Phase Signature " (CPS), is a function of the window orientation made up by a set of pulses whose locations depend on the constellation. If the constellation is known, the CPS is known, and the estimated frequency offset is the one such that the preliminary frequency compensation of the non linearly transformed signal samples provides the best match between the observed phase histogram and its expected value corresponding to zero frequency offset. The performance analysis is shown to match the numerical simulations for medium to high values of SNR. copyright by EURASIP
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