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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2074/1927
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Full metadata record
| DC Field | Value | Language |
|---|
| contributor.author | Fazle Azeem, M | - |
| contributor.author | Hanmandlu, M | - |
| contributor.author | Ahmad, N | - |
| date.accessioned | 2006-07-03T04:32:24Z | - |
| date.available | 2006-07-03T04:32:24Z | - |
| date.issued | 1998 | - |
| identifier.citation | TENCON IEEE Region 10 International Conference on Global Connectivity in Energy, Computer, Communication and Control, 1, 230 - 233p. | en |
| identifier.uri | http://eprint.iitd.ac.in/dspace/handle/2074/1927 | - |
| description.abstract | The concept of the approximate fuzzy data model (AFDM) is introduced. An attempt is made for input variable identification for fuzzy modeling of dynamical systems using the fuzzy curve, which is the output of AFDM. An output ratio is defined based on AFDM and system output that gives rise to the proposed criteria whose effectiveness is demonstrated by experimentation on mathematical models as well as by simulation on a few examples of dynamical systems. The proposed criteria thus serve as a significance test for the identification of inputs that actually affect the output | en |
| format.extent | 42584 bytes | - |
| format.mimetype | application/pdf | - |
| language.iso | en | en |
| subject | approximate fuzzy data model | en |
| subject | dynamical systems | en |
| title | A new criteria for input variable identification of dynamical systems | en |
| type | Article | en |
| Appears in Collections: | Electrical Engineering
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| File |
Description |
Size | Format |
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| azeemnew1998.pdf | | 41Kb | Adobe PDF | View/Open |
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