Analog nonderivative optimizers
| Contribuinte(s) |
Universidade Estadual Paulista (UNESP) |
|---|---|
| Data(s) |
27/05/2014
27/05/2014
01/01/1997
|
| Resumo |
Analog networks for solving convex nonlinear unconstrained programming problems without using gradient information of the objective function are proposed. The one-dimensional net can be used as a building block in multi-dimensional networks for optimizing objective functions of several variables. |
| Formato |
3592-3596 |
| Identificador |
http://dx.doi.org/10.1109/ACC.1997.609492 Proceedings of the American Control Conference, v. 6, p. 3592-3596. 0743-1619 http://hdl.handle.net/11449/64990 10.1109/ACC.1997.609492 WOS:A1997BJ29B00769 2-s2.0-0030686202 |
| Idioma(s) |
eng |
| Relação |
Proceedings of the American Control Conference |
| Direitos |
closedAccess |
| Palavras-Chave | #Nonlinear programming #Object oriented programming #Problem solving #Analog nonderivative optimizers #Optimization |
| Tipo |
info:eu-repo/semantics/conferencePaper |
