Asian Science Citation Index is committed to provide an authoritative, trusted and significant information by the coverage of the most important and influential journals to meet the needs of the global scientific community.  
ASCI Database
308-Lasani Town,
Sargodha Road,
Faisalabad, Pakistan
Fax: +92-41-8815544
Contact Via Web
Suggest a Journal
Information Technology Journal
Year: 2012  |  Volume: 11  |  Issue: 11  |  Page No.: 1655 - 1659

A Neural Network Model for Equality and Inequality Constrained Minimax Problems

Long-Hua Ma, Yu Zhang, Chun-Ning Yang and Hui Li    

Abstract: For signal processing and process control, the minimax problem is a crucial point in research subjects. But efficient solutions to equality and inequality constrained nonlinear general minimax problems are relatively scarce. A minimax neural network model was proposed to solve the general minimax problem based on penalty function. In this model, the unique requirement is that the objective function and constraint functions should be first-order differentiable. In addition to the global stability analysis based on the Lyapunov function, the proposed model was simulated and its validity was evaluated with numerical results. Experimental results demonstrated that the proposed minimax neural network model can solve the problem in seconds which is more efficient than the conventional genetic algorithm and simplex genetic algorithms.

Cited References   |    Fulltext    |   Related Articles   |   Back
   
 
 
 
  Related Articles

 
 
 
 
 
 
 
 
 
Copyright   |   Desclaimer   |    Privacy Policy   |   Browsers   |   Accessibility