Abstract
A unified procedure based on K-L expansion to simulate stationary and non-stationary, Gaussian and non-Gaussian processes has earlier been proposed by the authors. As an extension to the unified simulation procedure, this paper adopts the wavelet-Galerkin approach to solve Fredholm integral equation to improve the performance of the K-L method. The validity and convergence characteristics of the wavelet-Garlekin method for solving integral equations are illustrated using the non-stationary Wiener process. The wavelet-Galerkin solutions are more accurate and faster to compute than those derived using the conventional Garlerkin method. This ability to compute a very large number of K-L terms rapidly and accurately provides a practical and direct means of overcoming known K-L limitations associated with non-smooth covariance functions and long weakly-correlated processes.