IEICE TRANSACTIONS on Fundamentals
Fast Simulation Technique of Plane Circuits via Two-Layer CNN-Based Modeling
Summary :
A fast time-domain simulation technique of plane circuits via two-layer Cellular Neural Network (CNN)-based modeling, which is necessary for power/signal integrity evaluation in VLSIs, printed circuit boards, and packages, is presented. Using the new notation expressed by the two-layer CNN, 1,553 times faster simulation is achieved, compared with Berkeley SPICE (ngspice). In CNN community, CNNs are generally simulated by explicit numerical integration such as the forward Euler and Runge-Kutta methods. However, since the two-layer CNN is a stiff circuit, we cannot analyze it by using an explicit numerical integration method. Hence, to analyze the two-layer CNN and reduce the computational cost, the leapfrog method is introduced. This procedure would open an application of CNN to electronic design automation area.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E91-A No.12 pp.3757-3762
- Publication Date
- 2008/12/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1093/ietfec/e91-a.12.3757
- Type of Manuscript
- PAPER
- Category
- Nonlinear Problems
Authors
Keyword
Latest Issue
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Yuichi TANJI, Hideki ASAI, Masayoshi ODA, Yoshifumi NISHIO, Akio USHIDA, "Fast Simulation Technique of Plane Circuits via Two-Layer CNN-Based Modeling" in IEICE TRANSACTIONS on Fundamentals,
vol. E91-A, no. 12, pp. 3757-3762, December 2008, doi: 10.1093/ietfec/e91-a.12.3757.
Abstract: A fast time-domain simulation technique of plane circuits via two-layer Cellular Neural Network (CNN)-based modeling, which is necessary for power/signal integrity evaluation in VLSIs, printed circuit boards, and packages, is presented. Using the new notation expressed by the two-layer CNN, 1,553 times faster simulation is achieved, compared with Berkeley SPICE (ngspice). In CNN community, CNNs are generally simulated by explicit numerical integration such as the forward Euler and Runge-Kutta methods. However, since the two-layer CNN is a stiff circuit, we cannot analyze it by using an explicit numerical integration method. Hence, to analyze the two-layer CNN and reduce the computational cost, the leapfrog method is introduced. This procedure would open an application of CNN to electronic design automation area.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e91-a.12.3757/_p
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@ARTICLE{e91-a_12_3757,
author={Yuichi TANJI, Hideki ASAI, Masayoshi ODA, Yoshifumi NISHIO, Akio USHIDA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Fast Simulation Technique of Plane Circuits via Two-Layer CNN-Based Modeling},
year={2008},
volume={E91-A},
number={12},
pages={3757-3762},
abstract={A fast time-domain simulation technique of plane circuits via two-layer Cellular Neural Network (CNN)-based modeling, which is necessary for power/signal integrity evaluation in VLSIs, printed circuit boards, and packages, is presented. Using the new notation expressed by the two-layer CNN, 1,553 times faster simulation is achieved, compared with Berkeley SPICE (ngspice). In CNN community, CNNs are generally simulated by explicit numerical integration such as the forward Euler and Runge-Kutta methods. However, since the two-layer CNN is a stiff circuit, we cannot analyze it by using an explicit numerical integration method. Hence, to analyze the two-layer CNN and reduce the computational cost, the leapfrog method is introduced. This procedure would open an application of CNN to electronic design automation area.},
keywords={},
doi={10.1093/ietfec/e91-a.12.3757},
ISSN={1745-1337},
month={December},}
Copy
TY - JOUR
TI - Fast Simulation Technique of Plane Circuits via Two-Layer CNN-Based Modeling
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 3757
EP - 3762
AU - Yuichi TANJI
AU - Hideki ASAI
AU - Masayoshi ODA
AU - Yoshifumi NISHIO
AU - Akio USHIDA
PY - 2008
DO - 10.1093/ietfec/e91-a.12.3757
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E91-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2008
AB - A fast time-domain simulation technique of plane circuits via two-layer Cellular Neural Network (CNN)-based modeling, which is necessary for power/signal integrity evaluation in VLSIs, printed circuit boards, and packages, is presented. Using the new notation expressed by the two-layer CNN, 1,553 times faster simulation is achieved, compared with Berkeley SPICE (ngspice). In CNN community, CNNs are generally simulated by explicit numerical integration such as the forward Euler and Runge-Kutta methods. However, since the two-layer CNN is a stiff circuit, we cannot analyze it by using an explicit numerical integration method. Hence, to analyze the two-layer CNN and reduce the computational cost, the leapfrog method is introduced. This procedure would open an application of CNN to electronic design automation area.
ER -
English
