基于人工神经网络的纳米级CMOS压控振荡器统计仿真与建模

S. Mandal, Soumya Pandit
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摘要

模内工艺参数的变化对模拟/射频电路的成品率有重要影响。本文给出了工艺参数变化对纳米级CMOS压控振荡器电路影响的统计结果。利用人工神经网络建立了工艺参数变化与性能变化的统计模型。所构建的模型具有与蒙特卡罗分析技术相似的精度,但所耗费的时间要少得多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Statistical Simulation and Modeling of Nano-scale CMOS VCO Using Artificial Neural Network
The variation of intra-die process parameters play a significant role in determining the yield of an analog/RF circuit. This paper presents statistical results demonstrating the effect of variations of process parameters on a nano-scale CMOS voltage controlled oscillator circuit. A statistical model relating the process parameter variations and the performance variations has been constructed using artificial neural network. The constructed model shows accuracy similar to that obtained though Monte Carlo analysis technique, however, consuming much less time.
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