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Behavioral-level performance modeling of analog and mixed-signal systems using support vector machines

机译:使用支持向量机的模拟和混合信号系统的行为级性能建模

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This paper presents a novel behavioral-level analog and mixed-signal (AMS) system performance modeling methodology using support vector machines (SVM). The method relies on linearly graded sub-spaces to model complex multi-dimensional performance spaces. A detailed evaluation of the method has been carried out for the purpose of potential use for AMS synthesis. The method has been applied to a complex non-ideal 2nd order Sigma-Delta modulator (SDM) and results show good accuracy of performance modeling and numerical efficiency.
机译:本文提出了一种新颖的行为级模拟和混合信号(AMS)系统性能建模方法,使用支持向量机(SVM)。该方法依赖于线性分级的子空间来模拟复杂的多维性能空间。已经对AMS合成的潜在使用进行了对该方法的详细评估。该方法已应用于复杂的非理想2nd订单Sigma-Delta调制器(SDM),结果显示出良好的性能建模和数值效率。

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