最小化容错对细胞神经网络硬件实现的影响

1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359) Pub Date : 1998-04-14 DOI:10.1109/CNNA.1998.685407

R. Tetzlaff, R. Kunz, G. Geis, D. Wolf

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引用次数: 6

摘要

本文提出了一种最小化细胞神经网络(CNN)芯片容差故障影响的方法。将仿真系统SCNN与“CNN原型系统”连接，对cp300 CNN芯片的参数值进行调整。结果显示了VLSI芯片的错误输出，并提出了一种适合的方法来直接调整参数以实现CNN。

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Minimizing the effects of tolerance faults on hardware realizations of cellular neural networks

In this paper a procedure for minimizing the effects of tolerance faults in cellular neural network (CNN) chips is presented. The simulation system SCNN was connected with the "CNN prototyping system" for adjusting the parameter values of the cp300 CNN chip. Results showing the erroneous outputs of the VLSI chip are presented, together with a suitable way for adapting parameter directly to a CNN realization.

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1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)

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