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Process mismatch analysis based on reduced-order models

机译:基于降阶模型的过程失配分析

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This paper describes a methodology based on reduced-order models to investigate the effects of process mismatch in analog circuits in the presence of reliability degradation. Neural network-based reduced-order models for the DC drain current, Ids, of 65 nm n- and p-channel transistors have been generated in terms of six process parameters, temperature, and device age. The models identify the contribution of process parameters to the mismatch of n- and p-channel transistors as they age. Hot carrier injection (HCI) is considered as the main reliability degradation for n-channel devices and negative bias temperature instability (NBTI) is considered for p-channel devices. It is demonstrated that the variations of the effective channel length and intrinsic threshold voltage are major contributors to device mismatch in the absence of aging. Finally, a beta multiplier current reference is analyzed using the developed models for the impact of process mismatch with and without the aging effects. It is shown that in a cascode current mirror the variability of the reference current can be reduced by ensuring that the same rail transistors experience similar variations.
机译:本文介绍了一种基于降阶模型的方法,以研究在可靠性降低的情况下模拟电路中工艺失配的影响。针对六个工艺参数,温度和器件寿命,已经针对65 nm n沟道和p沟道晶体管的直流漏极电流I ds 建立了基于神经网络的降阶模型。这些模型确定了随着n沟道和p沟道晶体管老化而导致的工艺参数失配。对于n沟道器件,热载流子注入(HCI)被认为是主要的可靠性下降,而对于p沟道器件,则考虑了负偏置温度不稳定性(NBTI)。结果表明,有效沟道长度和固有阈值电压的变化是在不存在老化的情况下导致器件失配的主要因素。最后,使用已开发的模型来分析β乘数电流参考,以了解有无老化影响的过程失配的影响。结果表明,在共源共栅电流镜中,可以通过确保相同的供电晶体管经历相似的变化来减小参考电流的变化。

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