Campuses:

oprimization

Thursday, January 28, 2016 - 11:30am - 12:20pm
Necmiye Ozay (University of Michigan)
This talk addresses the problem of robust identification and (in)validation of hybrid models from noisy data. Given some input/output data the goal is to infer the underlying dynamical system that can interpolate the data within a given noise bound or to check whether there is a model within a model family that can interpolate the data. We define suitable a priori model sets and objective functions that seek simple models which can capture the information sparsely encoded in the data streams.
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