Active Integrated Devices PDN Balanced Truncation Reduction Method

Na Gao; Shu Guo Xie

doi:10.4028/www.scientific.net/AMR.850-851.939

Paper Titles

The Passive Target Motion Parameters Estimate Algorithm Based on Particle Filter
p.922

Sensitivity Analysis to Attribute Values Based on Grey Correlation in Multiple Attribute Decision Making
p.927

Computing and Simulations of the Acoustic Scattering Field of Underwater Targets Based on the CM Method
p.932

Topology Identification and Adaptive Synchronization of Fractional-Order Complex Networks
p.936

Active Integrated Devices PDN Balanced Truncation Reduction Method
p.939

Under Sampling Stochastic Resonance for Detecting Weak Signal
p.944

An Efficient Sampling Method for the Interpolation/Extrapolation of Electromagnetic Responses in Time and Frequency Domain
p.949

Compressed Sensing Based-On Digital Multi-Channel Sampling for Signal Spectrum Detection
p.953

Design of Compressed Sampling System Based on Digital Pre-Random Filter
p.957

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 850-851Active Integrated Devices PDN Balanced Truncation...

Active Integrated Devices PDN Balanced Truncation Reduction Method

Abstract:

For EMC simulation, the vector fitting model is transformed into time domain state equation model. Then the system is balanced. Then the reduced model can be obtained by removing the states corresponding to the small HSV (Hankel Singular Values). The order of the reduced model is determined by the singular curvature spectrum. Finally, balanced truncation model reduction method is used on a sample chip PDN (Power Distribution Network) and compared with the performance of the AWE (Asymptotic Waveform Evaluation) method. Simulation results show that the proposed method can operate in a wide frequency range and has smaller error and faster speed.

You might also be interested in these eBooks

Advances in Applied Sciences and Manufacturing

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 850-851)

Pages:

939-943

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.850-851.939

Citation:

Cite this paper

Online since:

December 2013

Authors:

Na Gao*, Shu Guo Xie

Keywords:

Balanced Truncation, Electromagnetism Compatibility, Model Reduction, Singular Value Decomposition

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] C. R. Paul, Introduction to Electromagnetic Compatibility (2nd Edition), New Jersey: A John Wiley & Sons, (2006).

Google Scholar

[2] Yaolin Jiang, Model Order Reduction Method, In Chinese, Mechanical Industry Press, Beijing, (2006).

Google Scholar

[3] R. W. Freund, Efficient linear circuit analysis by Pade approximation via the Lanczos process, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systerms, 1995, 14(5): 639-649.

DOI: 10.1109/43.384428

Google Scholar

[4] A. Odabasioglu, M. Celik, and L. T. Pileggi, PRIMA: passive reduced-order interconnect macromodeling algorithm, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 1998, 17(8): 645-654.

DOI: 10.1109/43.712097

Google Scholar

[5] B. Moore, Principal component analysis in linear systems: Controllability, observability, and model reduction, IEEE Transactions on Automatic Control, 26(1): 17-32, (1981).

DOI: 10.1109/tac.1981.1102568

Google Scholar

[6] Xi Chen and Shuguo Xie. Active integrated devices PDN vector fitting modeling method, In Chinese, The Journal of Buaa, 2012, 32(5): 849-856.

Google Scholar