Referenced Items are not available for this document.
We propose a general method for nonlinear chemical/biochemical model reduction and identification, inspired by the concept of subspace identification. We propose to use artificial neural networks to find a nonlinear projection operator that serves to define the reduced state out of the full state or out of an input-output time series. We investigate the viability of the method for both deterministic and stochastic systems
Published in:
American Control Conference, 1999. Proceedings of the 1999
(Volume:3
)
Date of Conference: 1999
- Page(s):
- 1568 - 1572 vol.3
- Meeting Date :
- 02 Jun 1999-04 Jun 1999
- ISSN :
- 0743-1619
- Print ISBN:
- 0-7803-4990-3
- INSPEC Accession Number:
- 6376423
- Conference Location :
- San Diego, CA
- Digital Object Identifier :
- 10.1109/ACC.1999.786089
- Product Type:
- Conference Publications
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