Neural networks for nonlinear programming

The dynamics of the modified canonical nonlinear programming circuit are studied and how to guarantee the stability of the network's solution. By considering the total cocontent function, the solution of the canonical nonlinear programming circuit is reconciled with the problem being modeled. In addition, it is shown how the circuit can be realized using a neural network, thereby extending the results of D.W. Tank and J.J. Hopefield (ibid., vol.CAS-33, p.533-41, May 1986) to the general nonlinear programming problem.>