A fast algorithm is presented for statistical analysis of large microwave and high-speed circuits with multiple stochastic parameters. Using the proposed algorithm, a set of local reduced-order parameterized circuits are derived based on adaptive frequency sampling and implicit multi-moment matching projection techniques. The local models preserve the stochastic parameters as symbolic quantities. As a result, stochastic response of the circuit can be obtained by simulating the local reduced models instead of the original large system leading to significant reduction in the computational cost compared to traditional Monte-Carlo techniques.

Additional Metadata
Keywords implicit moment-matching, parameterized model-order reduction, Statistical simulation
Persistent URL dx.doi.org/10.1109/MWSYM.2016.7540401
Conference 2016 IEEE MTT-S International Microwave Symposium, IMS 2016
Citation
Tao, Y. (Ye), Farhan, M. (Mina), Nouri, B. (Behzad), Nakhla, M.S, & Achar, R. (2016). Efficient variability analysis using parameterized model-order reduction. In IEEE MTT-S International Microwave Symposium Digest. doi:10.1109/MWSYM.2016.7540401