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您的检索式：作者名="Navdeep Goel"
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| 1 | Analysis of PC6 window function using fractional Fourier transform显示文摘Fractional Fourier transform(FRFT)is a linear transform generalizing Fourier transform(FT)that plays an important role in the field of signal processing and analysis.FRFT contains an adjustable parameterα,which it rotates the signal in the time frequency plane and represents the signal in an intermediate domain between time and frequency.FRFT provides a measure about the angular distribution of signal’s energy in time frequency plane.FT is a special case of FRFT when angleαis equal toπ/2.This paper presents mathematical model for obtaining FRFT of PC6 window function.The different parameters of this window function are also obtained with the help of simulation results.A comparison of window function parameters is presented using FT and FRFT.Also comparison of this window function with Hanning window function is presented in terms of Side Lobe Fall off Rate(SLFOR).For different values of FRFT order,PC6 window function shows variation in different parameters.Thus by changing the FRFT order,the minimum stop band attenuation of the resulting window function can be controlled. | Navdeep Goel Jaspinder Kaur | 2018 | 光电工程2018，45，6： | 0 |
| 2 | Quantitative SNR analysis of QFM signals in the LPFT domain with Gaussian windows显示文摘The purpose of this paper is to present a quantitative SNR analysis of quadratic frequency modulated(QFM) signals. This analysis is located in the continuous-time local polynomial Fourier transform(LPFT) domain using a Gaussian window function based on the definition of 3 dB signal-to-noise ratio(SNR).First, the maximum value of the local polynomial periodogram(LPP), and the 3 dB bandwidth in the LPFT domain for a QFM signal is derived, respectively. Then, based on these results, the 3 dB SNR of a QFM signal with Gaussian window function is given in the LPFT domain with one novel idea highlighted: the relationship among standard SNR, parameters of QFM signals and Gaussian window function is clear, and the potential application is demonstrated in the parameter estimation of a QFM signal using the LPFT.Moreover, the 3 dB SNR in the LPFT domain is compared with that in the linear canonical transform(LCT) domain. The validity of theoretical derivations is confirmed via simulation results. It is shown that,in terms of SNR, QFM signals in the LPFT domain can achieve a significantly better performance than those in the LCT domain. | Yan-Na ZHANG Bing-Zhao LI Navdeep GOEL Salvador GABARDA | 2019 | Science China(Information Sciences)2019，62，2： | 0 |
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