A high‐precision adaptive blind estimation method for chaotic time series

Abstract

To improve the estimation accuracy of chaotic time series and reduce the computational complexity, a high-precision adaptive blind estimation method is proposed. By introducing the pre-treatment method, the adaptive identification model is established, and the linear estimation equation is derived. Through the organic combination of the model and the least square mechanism, the complexity of the model is limited. When changing the type and length of the sequence, the parameters can be changed adaptively, so as to construct the corresponding trajectory equation and realize the blind estimation of chaotic time series. The analysis and experimental results show that the estimation accuracy of this method can reach 10–16 order of magnitude.