We present a linearly regressive prediction model for noisy chaotic time series phase space based on variational Bayesian and phase space reconstructive theory.
基于变分贝叶斯及相空间重构理论，提出了含噪混沌时间序列相空间域线性回归预测模型。
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It is intended to render a new sound theoretical basis for FEM and other variational methods and a series of new ways for blade design and modification.
When generalized variational inequality problem is studied, one method called auxiliary principle is to construct a series of auxiliary problems to approximate the original solution;