Neural network method for solving the quadratic programming problems

According to the basic optimization principle of artificial neural networks, a Lagrange function based neural network model approach appropriate for quadratic programming problems is given. Stability and convergence of the neural network are investigated. Neural optimization strategy to improve the neural computing efficiency is studied. Simulation demonstrates that these neural networks can effectively solve quadratic programming problems. The new network is easy to construct with circuits, capable of achieving the exact solution.