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Item Autoregressive modeling of the Wigner-Ville distribution based on signal decomposition and modified group delay(2004) Nayak, M.B.; Narasimhan, S.V.An autoregressive modeling of the Wigner-Ville distribution (WVD), based on signal decomposition (SD) by a perfect reconstruction filter bank (PRFB) and the modified magnitude group delay function (MMGD), has been proposed. The SD and MMGD, respectively, reduce the existence of crossterms (without any time smoothing) and the Gibb's ripple effect (due to truncation of the WVD kernel, without applying any window), significantly. In view of this, the modeling is not affected by either the crossterms or the Gibb's ripple and the window that would have been used. The proposed method represents actual time-frequency information parsimoniously and compared to the existing WVD modeling methods, its performance is significantly better in terms of both time and frequency resolution (as there is no time and frequency smoothing) and noise immunity/variance and is computationally efficient. © 2003 Elsevier B.V. All rights reserved.Item A new approach for channel blind identification based on second order cyclostationary statistics and the group delay has been proposed. In this, two methods are proposed. In both the methods, the correction is applied to the basic phase estimate for both the poles and zeros, in the group delay domain. The basic phase estimate is derived from the spectral correlation density (SCD) of the system output. In the first method, the phase correction is based on magnitude group delay. In the second method, not only the phase correction but also an improved system magnitude estimate of better variance and frequency resolution is derived based on modified magnitude group delay. The results indicate a significant improvement in performance for both the methods. For the first method in the absence of noise, the percentage normalized mean square error is reduced by about 85% over that of the existing non-parametric method. The second method in the presence of noise (SNR=5 dB), provides a reduction of 74% over the existing non-parametric method and 57% over the existing combined parametric and non-parametric methods. © 2005 Elsevier B.V. All rights reserved.(Channel blind identification based on cyclostationarity and group delay) Narasimhan, S.V.; Hazarathaiah, M.; Giridhar, P.V.S.2005