Macro-modeling of non-linear pre-emphasis differential driver circuits

Bhyrav Mutnury; Madhavan Swaminathan; Moises Cases; Nam Pham; Daniel De Araujo; Erdem Matoglu

doi:10.1109/MWSYM.2005.1517133

Macro-modeling of non-linear pre-emphasis differential driver circuits

Bhyrav Mutnury, Madhavan Swaminathan, Moises Cases, Nam Pham, Daniel De Araujo, Erdem Matoglu

Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

Differential signaling has become important in high speed digital and mixed signal systems because of its numerous advantages over single-ended signaling. Differential signaling reduces effects like Simultaneous Switching Noise (SSN), Electro Magnetic Interference (EMI) and crosstalk coupling. Signal Integrity (SI) and timing analysis using differential drivers is computationally exhaustive due to increased complexity in design that includes features such as precompensation and slew rate control. Therefore, accurate macro-modeling of differential driver circuits for a quality design is a huge challenge. In this paper, a modeling technique based on Recurrent Neural Network (RNN) is proposed to model differential driver circuits with and without pre-emphasis. Good accuracy is obtained in the test cases shown for the proposed modeling methodology at minimum computational cost.

Original language	English (US)
Title of host publication	2005 IEEE MTT-S International Microwave Symposium Digest
Pages	1987-1990
Number of pages	4
DOIs	https://doi.org/10.1109/MWSYM.2005.1517133
State	Published - 2005
Event	2005 IEEE MTT-S International Microwave Symposium - Long Beach, CA, United States Duration: Jun 12 2005 → Jun 17 2005

Publication series

Name	IEEE MTT-S International Microwave Symposium Digest
Volume	2005
ISSN (Print)	0149-645X

Other

Other	2005 IEEE MTT-S International Microwave Symposium
Country/Territory	United States
City	Long Beach, CA
Period	6/12/05 → 6/17/05

All Science Journal Classification (ASJC) codes

Radiation
Condensed Matter Physics
Electrical and Electronic Engineering

Access to Document

10.1109/MWSYM.2005.1517133

Cite this

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title = "Macro-modeling of non-linear pre-emphasis differential driver circuits",

abstract = "Differential signaling has become important in high speed digital and mixed signal systems because of its numerous advantages over single-ended signaling. Differential signaling reduces effects like Simultaneous Switching Noise (SSN), Electro Magnetic Interference (EMI) and crosstalk coupling. Signal Integrity (SI) and timing analysis using differential drivers is computationally exhaustive due to increased complexity in design that includes features such as precompensation and slew rate control. Therefore, accurate macro-modeling of differential driver circuits for a quality design is a huge challenge. In this paper, a modeling technique based on Recurrent Neural Network (RNN) is proposed to model differential driver circuits with and without pre-emphasis. Good accuracy is obtained in the test cases shown for the proposed modeling methodology at minimum computational cost.",

author = "Bhyrav Mutnury and Madhavan Swaminathan and Moises Cases and Nam Pham and {De Araujo}, Daniel and Erdem Matoglu",

year = "2005",

doi = "10.1109/MWSYM.2005.1517133",

language = "English (US)",

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series = "IEEE MTT-S International Microwave Symposium Digest",

pages = "1987--1990",

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note = "2005 IEEE MTT-S International Microwave Symposium ; Conference date: 12-06-2005 Through 17-06-2005",

}

Mutnury, B, Swaminathan, M, Cases, M, Pham, N, De Araujo, D & Matoglu, E 2005, Macro-modeling of non-linear pre-emphasis differential driver circuits. in 2005 IEEE MTT-S International Microwave Symposium Digest., 1517133, IEEE MTT-S International Microwave Symposium Digest, vol. 2005, pp. 1987-1990, 2005 IEEE MTT-S International Microwave Symposium, Long Beach, CA, United States, 6/12/05. https://doi.org/10.1109/MWSYM.2005.1517133

Macro-modeling of non-linear pre-emphasis differential driver circuits. / Mutnury, Bhyrav; Swaminathan, Madhavan; Cases, Moises et al.
2005 IEEE MTT-S International Microwave Symposium Digest. 2005. p. 1987-1990 1517133 (IEEE MTT-S International Microwave Symposium Digest; Vol. 2005).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Macro-modeling of non-linear pre-emphasis differential driver circuits

AU - Mutnury, Bhyrav

AU - Swaminathan, Madhavan

AU - Cases, Moises

AU - Pham, Nam

AU - De Araujo, Daniel

AU - Matoglu, Erdem

PY - 2005

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N2 - Differential signaling has become important in high speed digital and mixed signal systems because of its numerous advantages over single-ended signaling. Differential signaling reduces effects like Simultaneous Switching Noise (SSN), Electro Magnetic Interference (EMI) and crosstalk coupling. Signal Integrity (SI) and timing analysis using differential drivers is computationally exhaustive due to increased complexity in design that includes features such as precompensation and slew rate control. Therefore, accurate macro-modeling of differential driver circuits for a quality design is a huge challenge. In this paper, a modeling technique based on Recurrent Neural Network (RNN) is proposed to model differential driver circuits with and without pre-emphasis. Good accuracy is obtained in the test cases shown for the proposed modeling methodology at minimum computational cost.

AB - Differential signaling has become important in high speed digital and mixed signal systems because of its numerous advantages over single-ended signaling. Differential signaling reduces effects like Simultaneous Switching Noise (SSN), Electro Magnetic Interference (EMI) and crosstalk coupling. Signal Integrity (SI) and timing analysis using differential drivers is computationally exhaustive due to increased complexity in design that includes features such as precompensation and slew rate control. Therefore, accurate macro-modeling of differential driver circuits for a quality design is a huge challenge. In this paper, a modeling technique based on Recurrent Neural Network (RNN) is proposed to model differential driver circuits with and without pre-emphasis. Good accuracy is obtained in the test cases shown for the proposed modeling methodology at minimum computational cost.

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Macro-modeling of non-linear pre-emphasis differential driver circuits

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