Concurrent MultiParameter Learning Demonstrated on the Kuramoto--Sivashinsky Equation

We develop an algorithm based on the nudging data assimilation scheme for concurrent (on-the-fly) estimation of scalar parameters a system evolutionary dissipative partial differential equations in which state is partially observed. The takes advantage error that results from with incorrect true system. intuitive nature makes its extension to several different systems immediate, and it allows recovery multiple simultaneously. test method Kuramoto--Sivashinsky equation one dimension demonstrate efficacy this context.