Estimation of instantaneous frequencies using iterative empirical mode decomposition

A novel instantaneous frequency-based time-frequency representation is proposed for the analysis of multicomponent signals. The concept of frequency translation is innovatively combined with the empirical mode decomposition algorithm to formulate an iterative procedure, referred to as the iterative empirical mode decomposition, to separate the components present in a signal at a suitably selected frequency resolution. The instantaneous frequency and amplitude estimated on the separated components are used to form the new time-frequency representation. The iterative empirical mode decomposition is assessed for component resolvability, and the performance of the aforementioned time-frequency representation is compared with several other time-frequency representations based on visual inspection and using objective criteria. The Hilbert spectrum formed using the iterative empirical mode decomposition not only provides high concentration of energy about the components' instantaneous frequencies at high signal-to-noise ratio, but also good resolution while keeping the interference terms at a minimum.