Varying Wave-Shape Component Decomposition: Algorithm and Applications

The decomposition problem for multiple sinusoidal component signals has been developed in the past decades. However, many complex time series are made up of wave-shape components, which invalidates signal decomposition methods based on sinusoidal components. Since wave-shape components are time-varying from one cycle to the other and often contaminated by strong noise, robustly decomposing a signal into wave-shape components is still a challenging task. In this article, a varying wave-shape component decomposition (VWCD) method is proposed to extract time-varying and weak characteristics of wave-shape components from a multicomponent signal. Specifically, instantaneous frequencies (IFs) of varying wave-shape components are no longer inter multiples of a fundamental IF allowing the VWCD method more flexible in practical applications. We propose an instantaneous amplitudes and fundamental component phases estimation method based on an intrinsic chirp signal model and a regression coefficients initialization method by a fixed wave-shape signal model. The potential and effectiveness of the proposed VWCD method are verified by some simulated signals with different signal-to-noise ratios, a real-world electroencephalography seizure signal, and an experimental chest wall vibration signal from a microwave vital sign monitoring system.

Automated summary

The decomposition problem for multiple sinusoidal component signals has been developed in the past decades. However, many complex time series are made up of wave-shape components, which invalidates signal decomposition methods based on sinusoidal components. In this article, a varying wave-shape component decomposition (VWCD) method is proposed to extract time-varying and weak characteristics of wave-shape components from a multicomponent signal. The potential and effectiveness of the proposed VWCD method are verified by some simulated signals with different signal-to-noise ratios, a real-world electroencephalography seizure signal, and an experimental chest wall vibration signal from a microwave vital sign monitoring system.