Kernel Approach to Autoregressive Modeling
نویسندگان
چکیده
A kernel-based approach for nonlinear modeling of time series data is proposed in this paper. Autoregressive modeling is achieved in a feature space defined by a kernel function using a linear algorithm. The method extends the advantages of the conventional autoregressive models to characterization of nonlinear signals through the intelligent use of kernel functions.Experiments with synthetic signals demonstrate that this method seems to be a promising alternative to nonlinear modeling schemes.
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