Abstract
A bootstrap method is presented for finding efficient sum-of-poles approximations of causal functions. The method is based on a recursive application of the nonlinear least squares optimization scheme developed in (Alpert et al. in SIAM J. Numer. Anal. 37:1138-1164, 2000), followed by the balanced truncation method for model reduction in computational control theory as a final optimization step. The method is expected to be useful for a fairly large class of causal functions encountered in engineering and applied physics. The performance of the method and its application to computational physics are illustrated via several numerical examples.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 16-39 |
| Number of pages | 24 |
| Journal | Journal of Scientific Computing |
| Volume | 55 |
| Issue number | 1 |
| DOIs | |
| State | Published - Apr 2013 |
All Science Journal Classification (ASJC) codes
- Software
- Theoretical Computer Science
- Numerical Analysis
- General Engineering
- Computational Theory and Mathematics
- Computational Mathematics
- Applied Mathematics
Keywords
- Balanced truncation method
- Model reduction
- Rational approximation
- Square root method
- Sum-of-poles approximation