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A generalized Volterra series method for reconstructing deterministic dynamics from noisy chaotic time series

机译:从噪声混沌时间序列重构确定性动力学的广义Volterra级数方法

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Many problems such as over-fitting and subset selection are introduced in the standard Volterra model (SVM) in reconstructing deterministic dynamics from noisy chaotic time series. An optimal transformed Volterra filtering (OTVF) with only a small number of Volterra terms able to reconstruct the underlying determinism was presented.
机译:标准Volterra模型(SVM)在从嘈杂的混沌时间序列重构确定性动力学中引入了许多问题,例如过度拟合和子集选择。提出了仅具有少量Volterra项就能重构基本确定性的最优变换Volterra滤波(OTVF)。

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