Publication | Closed Access
Families of moment matching-based reduced order models for linear descriptor systems
13
Citations
14
References
2016
Year
Unknown Venue
Moment-matching ProcedureReduced Order ModelingDescriptor SystemsEngineeringLow-rank ApproximationParametrized FamiliesStatistical Signal ProcessingPattern RecognitionSystems EngineeringMultilinear Subspace LearningEstimation TheorySignal ProcessingStatisticsLinear Descriptor Systems
In this paper a moment-matching procedure for descriptor systems is presented. Based on a time-domain notion of moments, parametrized families of reduced order models matching the moments of the original system are derived. An example of exploiting the flexibility of choosing the free matrix parameters is demonstrated by achieving two-sided moment matching, i.e., obtaining reduced order models of order ν matching 2ν moments. In this context, a connection with the Loewner framework is shown which is a special case of the framework presented in this paper.
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