An Approach Based On Linear Differential Operator To Adaptive Signal Separation

In recent years, Single channel signal separation has attracted a great deal of attention because it has affected many applications. In the discipline of signal processing, the research of the signal’s representation and decomposition is always a fundamental problem. The methods used to separate signals vary because the different definitions of subcomponents are used. Among those approaches, the Empirical Mode Decomposition (EMD) and operator-based method are of particular interest to us, since both of them are self-adaptive and data-driven approaches.In this paper, we improved the Null Space Pursuit. The operator-based signal separation approach uses an adaptive operator to separate a signal into additive subcomponents which are in the null space of a high order in linear differential operator.The main work of this paper is as follows:Firstly, according to the Null Space Pursuit algorithm, we improved third-order operator and proposed tracking algorithm based on third-order linear differential operator zero space.Secondly, we improved fourth-order operator and proposed tracking algorithm based on third-order linear differential operator zero space according to the Null Space Pursuit algorithm.Finally, according to the experimental results, Compared the effect of signal decomposition based on different algorithms, we can conclude that the improved algorithm is better in denoising and decomposition those signals. We demonstrate the usefulness of the improved algorithm.