Otro
Analog nonderivative optimizers
Registro en:
Proceedings of the American Control Conference, v. 6, p. 3592-3596.
0743-1619
10.1109/ACC.1997.609492
WOS:A1997BJ29B00769
2-s2.0-0030686202
Autor
Teixeira, Marcelo C M
Zak, Stanislaw H.
Resumen
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.