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

被引：0

作者：

Pei, WJ ^{[1
]}

He, ZY ^{[1
]}

Yang, LX ^{[1
]}

Song, AG ^{[1
]}

Hull, SS ^{[1
]}

Cheung, JY ^{[1
]}

机构：

[1] SE Univ, Dept Radio Engn, Nanjing 210096, Peoples R China

来源：

APCCAS 2002: ASIA-PACIFIC CONFERENCE ON CIRCUITS AND SYSTEMS, VOL 2, PROCEEDINGS | 2002年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Many problems such as over-fitting and subset selection will be introduced in 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.

引用

页码：491 / 494

页数：4

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