File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Scopus: eid_2-s2.0-0032207947
- WOS: WOS:000077021500015
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Robust approximate pole assignment for second-order systems: Neural network computation
Title | Robust approximate pole assignment for second-order systems: Neural network computation |
---|---|
Authors | |
Issue Date | 1998 |
Citation | Journal Of Guidance, Control, And Dynamics, 1998, v. 21 n. 6, p. 923-928 How to Cite? |
Abstract | A recurrent neural network approach to robust approximate pole assignment for second-order systems is proposed. The design is formulated as an unconstrained optimization problem and solved via the gradient-flow approach, which is ideally suited for neural network implementation. Convergence of the gradient flow also is established. Simulation results are used to demonstrate the effectiveness of the proposed method. |
Persistent Identifier | http://hdl.handle.net/10722/156488 |
ISSN | 2023 Impact Factor: 2.3 2023 SCImago Journal Rankings: 1.092 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ho, DWC | en_US |
dc.contributor.author | Lam, J | en_US |
dc.contributor.author | Xu, J | en_US |
dc.date.accessioned | 2012-08-08T08:42:39Z | - |
dc.date.available | 2012-08-08T08:42:39Z | - |
dc.date.issued | 1998 | en_US |
dc.identifier.citation | Journal Of Guidance, Control, And Dynamics, 1998, v. 21 n. 6, p. 923-928 | en_US |
dc.identifier.issn | 0731-5090 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/156488 | - |
dc.description.abstract | A recurrent neural network approach to robust approximate pole assignment for second-order systems is proposed. The design is formulated as an unconstrained optimization problem and solved via the gradient-flow approach, which is ideally suited for neural network implementation. Convergence of the gradient flow also is established. Simulation results are used to demonstrate the effectiveness of the proposed method. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | Journal of Guidance, Control, and Dynamics | en_US |
dc.title | Robust approximate pole assignment for second-order systems: Neural network computation | en_US |
dc.type | Article | en_US |
dc.identifier.email | Lam, J:james.lam@hku.hk | en_US |
dc.identifier.authority | Lam, J=rp00133 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.scopus | eid_2-s2.0-0032207947 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-0032207947&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.volume | 21 | en_US |
dc.identifier.issue | 6 | en_US |
dc.identifier.spage | 923 | en_US |
dc.identifier.epage | 928 | en_US |
dc.identifier.isi | WOS:000077021500015 | - |
dc.publisher.place | United States | en_US |
dc.identifier.scopusauthorid | Ho, DWC=7402971938 | en_US |
dc.identifier.scopusauthorid | Lam, J=7201973414 | en_US |
dc.identifier.scopusauthorid | Xu, J=35276508700 | en_US |
dc.identifier.issnl | 0731-5090 | - |