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Two-dimensional spatio-temporal dynamics of analog image processing neural networks

机译:模拟图像处理神经网络的二维时空动力学

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A typical analog image-processing neural network consists of a 2D array of simple processing elements. When it is implemented with CMOS LSI, two dynamics issues naturally arise: (1) parasitic capacitors of MOS transistors induce temporal dynamics. Since a processed image is given as the stable equilibrium point of temporal dynamics, a temporally unstable chip is unusable; and (2) because of the array structure, the node voltage distribution induces spatial dynamics, and the node voltage distribution could behave in a wild manner which is undesirable for image-processing purposes. This paper derives several explicit formulas and relationships for the 2D dynamics, which are useful for the design and analysis of the class of networks of interest.
机译:典型的模拟图像处理神经网络由简单处理元素的2D阵列组成。当用CMOS LSI实现时,自然会产生两个动力学问题:(1)MOS晶体管的寄生电容器会引起时间动态变化。由于将处理后的图像作为时间动态的稳定平衡点,因此无法使用时间上不稳定的芯片。 (2)由于阵列结构,节点电压分布引起空间动力学,并且节点电压分布可能表现为狂野的方式,这对于图像处理目的是不希望的。本文为二维动力学导出了几个明确的公式和关系,这些公式和关系对于设计和分析感兴趣的网络类很有用。

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