TY - JOUR
T1 - Recurrent neural network for solving quadratic programming problems with equality constraints
AU - Wang, J.
PY - 1992/7/2
Y1 - 1992/7/2
N2 - A recurrent neural network for solving quadratic programming problems with equality constraints is presented. The proposed recurrent neural network is asymptotically stable and able to generate optimal solutions to quadratic programs with equality constraints. An opamp based analogue circuit realization of the recurrent neural network is described. An illustrative example is also discussed to demonstrate the performance and characteristics of the analogue neural network.
AB - A recurrent neural network for solving quadratic programming problems with equality constraints is presented. The proposed recurrent neural network is asymptotically stable and able to generate optimal solutions to quadratic programs with equality constraints. An opamp based analogue circuit realization of the recurrent neural network is described. An illustrative example is also discussed to demonstrate the performance and characteristics of the analogue neural network.
UR - http://www.scopus.com/inward/record.url?scp=0027109161&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0027109161&origin=recordpage
M3 - RGC 21 - Publication in refereed journal
VL - 28
SP - 1345
EP - 1347
JO - Electronics Letters
JF - Electronics Letters
SN - 0013-5194
IS - 14
ER -