Analog nonderivative optimizers

Actas de congresos

Date

1997-01-01

Registration in:

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

http://repositorioslatinoamericanos.uchile.cl/handle/2250/2552620

Author

Universidade Estadual Paulista (UNESP)

Institutions

Universidade Estadual Paulista (Brasil)

Abstract

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.

Subjects

Nonlinear programming

Object oriented programming

Problem solving

Analog nonderivative optimizers

Optimization

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