Title | Computationally efficient steady-state multiscale estimation for 1-D diffusion processes |
Publication Type | Journal Article |
Year of Publication | 2001 |
Authors | Ho, T. T., P. Fieguth, and A. S. Willsky |
Journal | Automatica |
Volume | 37 |
Pagination | 325 - 340 |
Keywords | diffusion, distributed parameter systems, dynamic estimation, multiscale realization |
Abstract | Conventional optimal estimation algorithms for distributed parameter systems have been limited due to their computational complexity. In this paper, we consider an alternative modeling framework recently developed for large-scale static estimation problems and extend this methodology to dynamic estimation. Rather than propagate estimation error statistics in conventional recursive estimation algorithms, we propagate a more compact multiscale model for the errors. In the context of 1-D diffusion which we use to illustrate the development of our algorithm, for a discretespace process of N points the resulting multiscale estimator achieves O(N log N) computational complexity (per time step) with near-optimal performance as compared to the O(N) complexity of the standard Kalman filter. |
DOI | 10.1016/S0005-1098(00)00174-6 |