Neural-based Transient Behavioral Modeling of IC Buffers for High-speed Interconnect Design

摘要：

Artificial neural networks (ANN) have gained attention as fast and flexible vehicles to microwave modeling and design. This paper reviews a recent advance of neural network modeling, I.e., state-space dynamic neural network (SSDNN) for transient behavioral modeling of high-speed nonlinear circuits. The SSDNN model can be directly trained from the input and output waveforms without relying on the circuit internal details. A training algorithm exploiting adjoint sensitivities is summarized for training the model in an efficient manner. An example of the SSDNN technique for IC buffer modeling and its use with transmission line elements in high-speed interconnect design are included.

作者: Yi Cao Qi-Jun Zhang Ihsan Erdin

作者单位: Department of Electronics, Carleton University, Ottawa, ON, K1S 5B6, Canada Nortel Networks, Ottawa, ON, Canada

会议类型: 国际会议

会议名称: Progress in Electromagnetics Research Symposium 2007(2007年电磁学研究新进展学术研讨会)(PIERS 2007)

会议地点: 北京

会议语种:英文

页码: 1977-1979

在线出版日期: 2007-03-26（万方平台首次上网日期，不代表论文的发表时间）