International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 39 - Number 2 |
Year of Publication: 2012 |
Authors: Mohd. Samar Ansari, Syed Atiqur Rahman |
10.5120/4796-7049 |
Mohd. Samar Ansari, Syed Atiqur Rahman . Non-Linear Feedback Neural Network for Solution of Quadratic Programming Problems. International Journal of Computer Applications. 39, 2 ( February 2012), 44-48. DOI=10.5120/4796-7049
This paper presents a recurrent neural circuit for solving quadratic programming problems. The objective is tominimize a quadratic cost function subject to linearconstraints. The proposed circuit employs non-linearfeedback, in the form of unipolar comparators, to introducetranscendental terms in the energy function ensuring fastconvergence to the solution. The proof of validity of the energy function is also provided. The hardware complexity of the proposed circuit comparesfavorably with other proposed circuits for the same task. PSPICE simulation results arepresented for a chosen optimization problem and are foundto agree with the algebraic solution.