Publication | Closed Access
Transient Simulation for High-Speed Channels with Recurrent Neural Network
32
Citations
12
References
2018
Year
Unknown Venue
EngineeringComputational NeuroscienceComputer ModelingNumerical SimulationComputer EngineeringSystems EngineeringSimulationRnn ModelingModeling And SimulationChannel ModelDeep LearningNeural Architecture SearchChannel CharacterizationRecurrent Neural NetworkIo BuffersCircuit SimulationAnalog Behavioral Modeling
Recent success of recurrent neural network (RNN) in modeling time sequence has drawn a lot of attentions across multiple fields. Prior works have shown that RNN modeling can be suitable and even powerful for macro-modeling in circuit simulation. In this work, we propose using RNN for high-speed channel simulation in the time domain, which can handle the nonlinear behaviors of the IO buffers. The numerical example has demonstrated the capability and the accuracy of the proposed approach. Through the numerical example, we investigate the multiple well-known RNN structures on their capability of accurate transient channel simulation. We also examine the tunable parameters in the RNN model such as the optimization method in dealing with nonlinearities.
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