A new approach to sparse decomposition of nonstationary signals with multiple scale structures using self-consistent nonlinear waves

A new method for signal decomposition is proposed and tested. Based on self-consistent nonlinear wave equations with self-sustaining physical mechanisms in mind, the new method is adaptive and particularly effective for dealing with synthetic signals consisting of components of multiple time scales. By formulating the method into an optimization problem and developing the corresponding algorithm and tool, we have proved its usefulness not only for analyzing simulated signals, but, more importantly, also for real clinical data.