Improved signal analysis performance at low sampling rates using raised cosine empirical mode decomposition

Successful signal analysis using the empirical mode decomposition (EMD) algorithm requires a high degree of oversampling. This requirement arises from the need to precisely identify the local extrema of the signal to recover the signal envelope using natural cubic spline interpolation. Here, an EMD algorithm is introduced that uses the raised cosine interpolant. Raised cosine interpolation allows high fidelity reconstruction of the signal envelope when the local extrema cannot be precisely identified owing to low sampling rates. The superior signal analysis performance of this technique at low sampling rates is demonstrated using synthetic signals.