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本文建立了一种扩散-集中神经网络以模拟视觉系统区分图形与背景的集体计算功能.大脑皮层上的神经细胞在外部环境刺激作用下呈现兴奋状态,这种兴奋性通过连接向相邻的神经细胞扩散.另一方面,为了表示刺激的位置信息和注视的区域,兴奋性又必须向受激励的细胞所在区域进行集中.神经活性的这种扩散-集中机制是大脑皮层细胞的基本活动规律之一.
In this paper, we establish a diffusion-centralized neural network to simulate the collective computing function of the visual system to distinguish the graphics from the background.The neurons in the cerebral cortex exhibit an excited state under the stimulation of the external environment, and this excitability is connected to the adjacent nerves On the other hand, excitability must be concentrated in the area where the stimulated cells are located, in order to indicate the stimulus location information and the area of interest.The diffusion of neural activity, the central mechanism of action, is the basic law of activity of the cerebral cortical cells one.