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Wavelet transform is used in signal processing to represent a statistical random signal in to various frequency components. The transform converts the signal into approximation coefficient and detail coefficients; the mean of each coefficient for a noiseless signal is ideally zero but the mean of the coefficients for a noisy signal is shifted from zero. The noise of a wireless channel can be reduced...
Spectral analysis is only applicable to stationary signals and most of the real signals in many practical applications are non-stationary. Time-frequency methods are applied to analyze non-stationary signals and this paper presents different time-frequency methods to analyze a modulated random signal through a multi-path fading channel with emphasis on time-varying power spectra. Short-time Fourier...
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