Title
Suboptimal algorithms for worst case identification and model validation
Document Type
Conference Proceeding
Publication Date
12-1-1993
Abstract
New algorithms based on convex programming are proposed for worst case system identification. The algorithms are optimal within a factor of two asymptotically. Further, model validation, or data consistency is embedded in the identification process. Explicit worst case identification error bounds in H∞ norm are also derived for both uniformly and nonuniformly spaced frequency response samples.
Publication Source (Journal or Book title)
Proceedings of the IEEE Conference on Decision and Control
First Page
539
Last Page
544
Recommended Citation
Gu, G. (1993). Suboptimal algorithms for worst case identification and model validation. Proceedings of the IEEE Conference on Decision and Control, 1, 539-544. Retrieved from https://repository.lsu.edu/eecs_pubs/386