Discrete-time signal processing
Discrete-time signal processing
Complex AM signal model for non-stationary signals
Signal Processing
Complex FM signal model for non-stationary signals
Signal Processing
Signal Analysis: Wavelets, Filter Banks, Time-Frequency Transforms and Applications
Signal Analysis: Wavelets, Filter Banks, Time-Frequency Transforms and Applications
Analysis and synthesis of multicomponent signals using positivetime-frequency distributions
IEEE Transactions on Signal Processing
Energy separation in signal modulations with application to speechanalysis
IEEE Transactions on Signal Processing
Estimation of amplitude and phase parameters of multicomponentsignals
IEEE Transactions on Signal Processing
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The discrete energy separation algorithm (DESA) together with the Gabor's filtering provides a standard approach to estimate the amplitude envelope (AE) and the instantaneous frequency (IF) functions of a multicomponent amplitude and frequency modulated (AM-FM) signal. The filtering operation introduces amplitude and phase modulations in the separated monocomponent signals, which may lead to an error in the final estimation of the modulation functions. In this paper, we have proposed a method called the Fourier-Bessel expansion-based discrete energy separation algorithm (FB-DESA) for component separation and estimation of the AE and IF functions of a multicomponent AM-FM signal. The FB-DESA method does not introduce any amplitude or phase modulation in the separated monocomponent signal leading to accurate estimations of the AE and IF functions. Simulation results with synthetic and natural signals are included to illustrate the effectiveness of the proposed method.