Smoothing for random fields modeled by partial differential equations

The authors present an efficient, numerically reliable smoothing algorithm for random fields modeled by linear, constant coefficient, partial differential equations. The estimate is computed from discrete measurements by using the discrete Fourier transform to convert the two-dimensional (2D) problem to a collection of uncoupled one-dimensional (1D) problems which are then solved using stable iterations.