Modeling of Non-Stationary Process by Modular Separation of Stability and Plasticity
نویسنده
چکیده
In this contribution we present a method for modeling a non-stationary process by a combination of fast learning and slowly learning modules, where the fast learning modules transform the input and output data for stable kernel module, which models a situation normalized to be stationary. The proposed method is applied in mod-eling a non-stationary chemical process.
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