Faculty Publications
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Item An improved system blind identification method based on second-order cyclostationary statistics and the properties of group delay, has been proposed. This is achieved by applying a correction to the estimated phase (by the spectral correlation density of the system output) for the poles, in the group delay domain. The results indicate a significant improvement in system blind identification, in terms of root mean square error. Depending upon the signal-to-noise ratio, the improvement in percentage normalized mean square error ranges between 20 and 50%.(Improved system blind identification based on second-order cyclostationary statistics: A group delay approach) Giridhar, P.V.S.; Narasimhan, S.V.2000Item 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.2005Item Improved phase estimation based on complete bispectrum and modified group delay(2008) Narasimhan, S.V.; Basumallick, N.; Chaitanya, R.In this paper, a new method for extracting the system phase from the bispectrum of the system output has been proposed. This is based on the complete bispectral data computed in the frequency domain and modified group delay. The frequency domain bispectrum computation improves the frequency resolution and the modified group delay reduces the variance preserving the frequency resolution. The use of full bispectral data also reduces the variance as it is used for averaging. For the proposed method at a signal to noise ratio of 5dB, the reduction in root mean square error is in the range of 1.5-7 times over the other methods considered. © 2008 Springer-Verlag London Limited.Item Feedback active noise control based on forward-backward LMS predictor(2013) Pavithra, S.; Narasimhan, S.V.In this paper, a new feedback active noise control (FBANC) system based on forward-backward error LMS (FBLMS) predictor is proposed. The misadjustment of the FBLMS predictor is about half that of the forward error LMS (FLMS) predictor. The new ANC system employs FBLMS predictors both for its main path (MP) predictor and for the noise canceler (NC) for the secondary path (SP) identification (SPI). To realize the MP predictor based on the FBLMS concept, a new FXLMS structure is proposed. But for the NC for the SPI, the FBLMS predictor is directly used. The MP predictor based on FBLMS reduces its misadjustment. Further the use of FBLMS predictor for the NC, as it gives a good prediction of primary noise component in the error (residual noise), improves the SNR for SPI. Thus, the improved SP estimate and the reduced misadjustment for the MP predictor achieved result in a significantly better overall noise reduction (of about 8 dB) over the ANC that uses the MP predictor and noise canceler for SPI, both based only on the forward error LMS algorithm. The computational load for the proposed algorithm is about twice that of FBANC that uses only forward error. © 2012 Springer-Verlag London Limited.