Modeling of power supply noise with non-linear drivers using recurrent neural network (RNN) models

被引:0
|
作者
Mutnury, B [1 ]
Swaminathan, M [1 ]
Cases, M [1 ]
Pham, N [1 ]
de Araujo, DN [1 ]
Matoglu, E [1 ]
机构
[1] Georgia Inst Technol, Sch Elect & Comp Engn, Atlanta, GA 30332 USA
关键词
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Recurrent Neural Network (RNN) functions can be used to model highly nonlinear driver circuits. In this paper, RNN modeling technique is extended to multiple ports to model both the power supply noise and the ground noise accurately. RNN driver models can be extended to multiple ports to capture sensitive effects like Simultaneous Switching Noise (SSN) accurately when multiple driver circuits are switching. A comparison study is performed on test cases between RNN models and transistor level driver circuits for accuracy and computational speed-up is performed on few test cases. Results show that RNN driver models have huge computational speed-up over transistor level driver circuits.
引用
收藏
页码:740 / 745
页数:6
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