Modeling of power supply noise with non-linear drivers using Recurrent Neural Network (RNN) models

Bhyrav Mutnury, Madhavan Swaminathan, Moises Cases, Nam Pham, Daniel N. De Araujo, Erdem Matoglu

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)740-745
Number of pages6
JournalProceedings - Electronic Components and Technology Conference
StatePublished - 2005
Event55th Electronic Components and Technology Conference, ECTC - Lake Buena Vista, FL, United States
Duration: May 31 2005Jun 4 2005

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering


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