Abstract
A high-order analog Hopfield neural network is incorporated to get optimal or near-optimal solutions to a kind of nonlinear programming problems. By employing the operational transconductance amplifier (OTA) and MOS transistors, the practical analog implementation of the neural network can be achieved. The convergence characteristics are demonstrated by computer simulations and two sufficient conditions for the proposed analog neural network to obtain the Lyapunov stable solutions are given.
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