Abstract
Hopfield neural network (HNN) is an efficient optimization model, but it easily produces random noise. White noise is an ideal model and is more convenient in the mathematical analysis. This paper presents a new model of Hopfield neural network which is called White Noise Hopfield Neural Network. By introducing the white noise to the Hopfield neural network, we analyze the impact of noise on the neural network. The examples of the functional optimization and the traveling salesman problem (TSP) show as long as the appropriate adjustment Signal Noise Ratio (SNR), the performance of Hopfield network model for optimization has been greatly improved.
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