Detecting Nonlinear Causality via Nonlinear Modeling
نویسنده
چکیده
We analyze a set of complex time series from the view point of nonlinear causality. The mathematical background for analyzing time series is an extension of embedding theories of autonomous systems to an input{output system. We consider that the existence of nonlinear causality can be detected by nonlinear predictability of input and output sequences. Several numerical examples are given for con rmation of the proposed framework.
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