Efficient Uncertainty Quantification for the Periodic Steady State of Forced and Autonomous Circuits
This brief proposes an uncertainty quantification method for the periodic steady-state (PSS) analysis with both Gaussian and non-Gaussian variations. Our stochastic testing formulation for the PSS problem provides superior efficiency over both Monte Carlo methods and existing spectral methods. The n...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers (IEEE)
2017
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| Online Access: | http://hdl.handle.net/1721.1/108267 https://orcid.org/0000-0002-5880-3151 |
| _version_ | 1811081553886838784 |
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| author | Maffezzoni, Paolo Elfadel, Ibrahim M. Zhang, Zheng El Moselhy, Tarek Ali Daniel, Luca |
| author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
| author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Maffezzoni, Paolo Elfadel, Ibrahim M. Zhang, Zheng El Moselhy, Tarek Ali Daniel, Luca |
| author_sort | Maffezzoni, Paolo |
| collection | MIT |
| description | This brief proposes an uncertainty quantification method for the periodic steady-state (PSS) analysis with both Gaussian and non-Gaussian variations. Our stochastic testing formulation for the PSS problem provides superior efficiency over both Monte Carlo methods and existing spectral methods. The numerical implementation of a stochastic shooting Newton solver is presented for both forced and autonomous circuits. Simulation results on some analog/RF circuits are reported to show the effectiveness of our proposed algorithms. |
| first_indexed | 2024-09-23T11:48:23Z |
| format | Article |
| id | mit-1721.1/108267 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:48:23Z |
| publishDate | 2017 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/1082672022-10-01T06:10:42Z Efficient Uncertainty Quantification for the Periodic Steady State of Forced and Autonomous Circuits Efficient Uncertainty Quantification for the Periodic Steady State of Forced and Autonomous Circuits Maffezzoni, Paolo Elfadel, Ibrahim M. Zhang, Zheng El Moselhy, Tarek Ali Daniel, Luca Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology. Research Laboratory of Electronics Daniel, Luca Zhang, Zheng El Moselhy, Tarek Ali Daniel, Luca This brief proposes an uncertainty quantification method for the periodic steady-state (PSS) analysis with both Gaussian and non-Gaussian variations. Our stochastic testing formulation for the PSS problem provides superior efficiency over both Monte Carlo methods and existing spectral methods. The numerical implementation of a stochastic shooting Newton solver is presented for both forced and autonomous circuits. Simulation results on some analog/RF circuits are reported to show the effectiveness of our proposed algorithms. 2017-04-19T19:04:09Z 2017-04-19T19:04:09Z 2013-09 Article http://purl.org/eprint/type/JournalArticle 1549-7747 1558-3791 http://hdl.handle.net/1721.1/108267 Zhang, Zheng; El-Moselhy, Tarek A.; Maffezzoni, Paolo; Elfadel, Ibrahim M. and Daniel, Luca. “Efficient Uncertainty Quantification for the Periodic Steady State of Forced and Autonomous Circuits.” IEEE Trans. Circuits Syst. II 60, no. 10 (October 2013): 687–691. © 2013 Institute of Electrical and Electronics Engineers (IEEE) https://orcid.org/0000-0002-5880-3151 en_US http://dx.doi.org/10.1109/TCSII.2013.2278110 IEEE Transactions on Circuits and Systems II: Express Briefs Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) Prof. Daniel via Phoebe Ayers |
| spellingShingle | Maffezzoni, Paolo Elfadel, Ibrahim M. Zhang, Zheng El Moselhy, Tarek Ali Daniel, Luca Efficient Uncertainty Quantification for the Periodic Steady State of Forced and Autonomous Circuits |
| title | Efficient Uncertainty Quantification for the Periodic Steady State of Forced and Autonomous Circuits |
| title_full | Efficient Uncertainty Quantification for the Periodic Steady State of Forced and Autonomous Circuits |
| title_fullStr | Efficient Uncertainty Quantification for the Periodic Steady State of Forced and Autonomous Circuits |
| title_full_unstemmed | Efficient Uncertainty Quantification for the Periodic Steady State of Forced and Autonomous Circuits |
| title_short | Efficient Uncertainty Quantification for the Periodic Steady State of Forced and Autonomous Circuits |
| title_sort | efficient uncertainty quantification for the periodic steady state of forced and autonomous circuits |
| url | http://hdl.handle.net/1721.1/108267 https://orcid.org/0000-0002-5880-3151 |
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