تجزیه حالت مجتمعی پیچیده برای برنامه های پردازش سیگنال

Complex-valued signals occur in many areas of science and engineering and are thus of fundamental interest. The complex variational mode decomposition (CVMD) is proposed as a natural and a generic extension of the original VMD algorithm for the analysis of complex-valued data in this work. Moreover, the equivalent filter bank structure of the CVMD in the presence of white noise, and the effects of initialization of center frequency on the filter bank property are both investigated via numerical experiments. Benefiting from the advantages of CVMD algorithm, its bi-directional Hilbert time-frequency spectrum is developed as well, in which the positive and negative frequency components are formulated on the positive and negative frequency planes separately. Several applications in the real-world complex-valued signals support the analysis.