SSA, SVD, QR-cp, and RBF Model Reduction
نویسندگان
چکیده
We propose an application of SVD model reduction to the class of RBF neural models for improving performance in contexts such as on-line prediction of time series. The SVD is coupled with QR-cp factorization. It has been found that such a coupling leads to more precise extraction of the relevant information, even when using it in an heuristic way. Singular Spectrum Analysis (SSA) and its relation to our method is also mentioned. We analize performance of the proposed on-line algorithm using a “benchmark” chaotic time series and a difficult-to-predict, dynamically changing series.
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