Polynomial Chaos Quadrature-based Minimum Variance Approach for Source Parameters Estimation
نویسندگان
چکیده
منابع مشابه
Polynomial Chaos Quadrature-based Minimum Variance Approach for Source Parameters Estimation
We present a polynomial chaos based minimum variance formulation to solve inverse problems. The utility of the proposed approach is evaluated by considering the ash transport problem arising due to volcanic eruption. Volcanic ash advisory centers generally makes use of mathematical models for column eruption and advection and diffusion of ash cloud in atmosphere. These models require input data...
متن کاملEfficient estimation of polynomial chaos proxies using generalized sparse quadrature
We investigate the use of sparse grid methods in computing polynomial chaos (PC) proxies for forward stochastic problems associated with numerically-expensive simulators. These are problems where some input parameters are random with known distributions, and stochastic properties of the simulator output are desired. The bottleneck for PC proxy construction is the estimation of the coefficients,...
متن کاملFast algorithms for least-squares-based minimum variance spectral estimation
The minimum variance (MV) spectral estimator is a robust high-resolution frequencydomain analysis tool for short data records. The traditional formulation of the minimum variance spectral estimation (MVSE) depends on the inverse of a Toeplitz autocorrelation matrix, for which a fast computational algorithm exists that exploits this structure. This paper extends the MVSE approach to two data-onl...
متن کاملLocal Polynomial Variance Function Estimation
The conditional variance function in a heteroscedastic, nonparametric regression model is estimated by linear smoothing of squared residuals. Attention is focussed on local polynomial smoothers. Both the mean and variance functions are assumed to be smooth, but neither is assumed to be in a parametric family. The eeect of preliminary estimation of the mean is studied, and a \degrees of freedom"...
متن کاملA polynomial chaos-based kalman filter approach for parameter estimation of mechanical systems
In this study, a new computational approach for parameter identification is proposed based on the application of the polynomial chaos theory. The polynomial chaos method has been shown to be considerably more efficient than Monte Carlo in the simulation of systems with a small number of uncertain parameters. In the new approach presented in this paper, the maxi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2012
ISSN: 1877-0509
DOI: 10.1016/j.procs.2012.04.122