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Description:
Our aim is to numerically solve parameter-dependent Lyapunov equations using reduced basis method. Such equations arise in parametric model order reduction. We restrict ourselves to systems that affinely depend on the parameter as our main ingredient is the min-Theta approach. In those cases, we derive various a posteriori error estimates. Based on these estimates, Greedy algorithms for constructing reduced basis are formulated. Thanks to the derived results, a novel so-called parametric balanced truncation model reduction method is developed. Numerical examples are presented.