中文说明：本文提出了基于 Langevin 方程与霍普费尔德模型相结合的两种简单的优化技术。 拟议的模式-称为随机模型 (SM) 和脉冲噪声模型 (国家)-可以视为简单随机扩展的优化网络。这两个模型按照随机神经网络 [14] 和扩散机 [23] 的想法。 他们不同窗体的所述的方法由噪声和他们注射的方式的性质。
English Description：
This paper presents two simple optimization techniques based on combining the Langevin Equation with the Hopfield Model. Proposed models - referred as Stochastic Model (SM) and Pulsed Noise Model (PNM) - can be viewed as straightforward stochastic extensions of the Hopfield optimization network. Both models follow the idea of Stochastic Neural Network [14] and Diffusion Machine [23]. They differ form the referred approaches by the nature of noises and the way of their injection.