Fast statistical analysis of nonlinear analog circuits using model order reduction-Reference-Cited by-同舟云学术

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Fast statistical analysis of nonlinear analog circuits using model order reduction

Published:2015-07-03 Issue:3 Volume:85 Page:379-394
ISSN:0925-1030
Container-title:Analog Integrated Circuits and Signal Processing
language:en
Short-container-title:Analog Integr Circ Sig Process

Author:

Aridhi Henda,Zaki Mohamed H.,Tahar Sofiène

Publisher

Springer Science and Business Media LLC

Subject

Surfaces, Coatings and Films,Hardware and Architecture,Signal Processing

Link

http://link.springer.com/content/pdf/10.1007/s10470-015-0588-x.pdf

Reference46 articles.

1. Kinget, P. R. (2005). Device mismatch and tradeoffs in the design of analog circuits. IEEE Journal of Solid-State Circuits, 40(6), 1212–1224. doi: 10.1109/JSSC.2005.848021 .

2. Zhigang, H., Tan, S. X. D., Shen, R., & Shi, G. (2011). Performance bound analysis of analog circuits considering process variations. In ACM/IEEE design automation conference (pp. 310–315). doi: 10.1145/2024724.2024799 .

3. Kuo, P. Y., Saibua, S., Huang, G., & Zhou, D. (2012). An efficient method for evaluating analog circuit performance bounds under process variations. IEEE Transactions on Circuits and Systems II, 59(6), 351–355. doi: 10.1109/TCSII.2012.2190872 .

4. Lahiouel, O., Aridhi, H., Zaki, M. H., & Tahar, S. (2014). Enabling the DC solutions characterization using a fuzzy approach. IEEE international conference on new circuits and systems (pp. 161–164). doi: 10.1109/NEWCAS.2014.6934008 .

5. Jacoboni, C., & Lugli, P. (1989). The Monte Carlo method for semiconductor device simulation. Vienna: Springer. doi: 10.1007/978-3-7091-6963-6 .

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