Kumar Vishwajeet

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Abstract—This paper focuses on the development of analytical methods for uncertainty quantification of the models obtained by the Eigensystem Realization Algorithm (ERA) to quantify the effect of noise in the input-output experimental data. Starting from first principles, analytical expressions are presented for the probability distribution of eigenvalues(More)
The accuracy and the computational complexity of a Gaussian mixture model depends upon the number of components. In a stochastic dynamical system, the number of these components must change over time to account for the change in the uncertainty over time. A new splitting technique is provided based on the minimization of Fokker Planck Kolmogorov Equation.(More)
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