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Modelling and control of complex nonlinear plants is a challenging area where learning systems, i.e. systems that construct a nonlinear plant model or controller based on measurement data, are a promising approach. However, in real-world applications, the measured samples are corrupted with noise and often the distribution of the samples does not cover all(More)
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