You are in the accessibility menu

Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/64990
Title: 
Analog nonderivative optimizers
Author(s): 
Institution: 
Universidade Estadual Paulista (UNESP)
ISSN: 
0743-1619
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.
Issue Date: 
1-Jan-1997
Citation: 
Proceedings of the American Control Conference, v. 6, p. 3592-3596.
Time Duration: 
3592-3596
Keywords: 
  • Nonlinear programming
  • Object oriented programming
  • Problem solving
  • Analog nonderivative optimizers
  • Optimization
Source: 
http://dx.doi.org/10.1109/ACC.1997.609492
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/64990
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

There are no files associated with this item.
Show full item record   View Statistics
 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.