| dc.creator |
Baturone, I. |
|
| dc.creator |
Sánchez-Solano, Santiago |
|
| dc.creator |
Barriga, Angel |
|
| dc.creator |
Huertas-Díaz, J. L. |
|
| dc.date |
2008-04-15T17:35:57Z |
|
| dc.date |
2008-04-15T17:35:57Z |
|
| dc.date |
1998-11 |
|
| dc.date.accessioned |
2017-01-31T01:02:23Z |
|
| dc.date.available |
2017-01-31T01:02:23Z |
|
| dc.identifier |
XIII Conference on Design of Circuits and Integrated Systems (DCIS’98), pp. 316-321, Madrid, November 17-20, 1998. |
|
| dc.identifier |
http://hdl.handle.net/10261/3599 |
|
| dc.identifier.uri |
http://dspace.mediu.edu.my:8181/xmlui/handle/10261/3599 |
|
| dc.description |
A fuzzy processor is programmed to provide anoptimum output for solving a given problem. It could theoretically solve any problem (from a static point of view) if it is an universal approximator. This paper
addresses the design of fuzzy processors aiming at a twofold objective: efficient adaptive approximation of different and even dynamically changing surfaces and hardware simplicity. Adequate programmable
parameters and a fully-parallel architecture are selected. Mixed-signal blocks based on digitally programmed
current mirrors are employed. Error-descent
learning algorithms for tuning are discussed. Adaptive behavior is illustrated with an application to the on-line identification of a nonlinear plant. |
|
| dc.description |
Peer reviewed |
|
| dc.format |
86294 bytes |
|
| dc.format |
application/pdf |
|
| dc.language |
eng |
|
| dc.rights |
openAccess |
|
| dc.subject |
Fuzzy processors |
|
| dc.subject |
Adaptive approximation |
|
| dc.subject |
Architecture design |
|
| dc.title |
Optimization of adaptive fuzzy processor design |
|
| dc.type |
Comunicación de congreso |
|