Multiple Minor Components Extraction in Parallel Based on Möller Algorithm

An MC (minor component) is usually referred to as the noise part of a time-varying signal. Extracting multiple MCs from an input signal is very useful in many practical applications. Compared with single MC estimating algorithms and subspace tracking algorithms, multiple MC extraction algorithms have a wider range of applications and greater research significance. To address the existing issues with multiple MC extraction algorithms, such as the need to estimate parameters in advance and with numerous constraints, this paper proposes a novel multiple MC extraction algorithm by adding a diagonal weighted matrix to the Möller algorithm. The proposed algorithm’s fixed points are analyzed using ODE (ordinary differential equation) methods, and it is demonstrated that the algorithm achieves stable convergence only when the weight matrix converges to the desired MCs of the signal. The simulation results illustrate the effectiveness of the proposed algorithm.