Raised cosine filter-based empirical mode decomposition

Abstract

The empirical mode decomposition (EMD) is a relatively new method to decompose multicomponent signals that requires no a priori knowledge about the components. In this study, a modified algorithm using raised cosine interpolation is proposed which the authors refer to as raised cosine empirical mode decomposition. The decomposition quality of this proposed technique is controllable via an adjustable parameter. This results in better performance than the original approach which produces faster convergence or lower final error under different conditions. An efficient fast Fourier transform-based implementation of the proposed technique is presented. The signal decomposition performance of the new algorithm is demonstrated by application to a variety of multicomponent signals and a comparison with EMD algorithm is presented. Computational complexity of the two techniques is compared.