基于CMOS技术的最小/最大细胞神经网络(MMCNNS)设计

Wen-Cheng Yen, Rongna Chen, Jui-Lin Lai
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引用次数: 2

摘要

提出了模糊细胞神经网络(FCNN)结构的第一个VLSI实现。最小/最大CNN (MMCNN)是ii型FCNN的一种特殊情况,它只包含局部最小和最大操作。由于MMCNN结构简单,非常适合在图像处理领域的VLSI实现。仅需要一个神经元细胞、两个乘法器和9个min/max电路即可实现所提出的MMCNN。在HSPICE仿真中成功验证了MMCNN在灰度数学形态学运算中的侵蚀和膨胀的正确作用。在各种信号处理应用中,fcnn在神经网络系统的VLSI实现中具有很大的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of MIN/MAX cellular neural networks (MMCNNS) in CMOS technology
The first VLSI implementation of the fuzzy cellular neural network (FCNN) structure is presented. The MIN/MAX CNN (MMCNN) is a special case of type-II FCNN, which consists only of local MIN and MAX operations. Due to the simple structure of the MMCNN, it is very suitable for VLSI implementation in image processing. Only one neuron cell, two multipliers, and nine min/max circuits realize the proposed MMCNN. Correct functions of the MMCNN in the erosion and dilation of the gray-scale mathematical morphology operation have been successfully verified in HSPICE simulation. FCNNs have great potential in the VLSI implementation of neural network systems in various signal processing applications.
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