Article

Newton: a library-based analytical synthesis tool for RF-MEMS resonators

Authors:

Michael S. McCorquodale,

James L. McCann,

Richard B. BrownAuthors Info & Claims

ASP-DAC '06: Proceedings of the 2006 Asia and South Pacific Design Automation Conference

Pages 279 - 284

https://doi.org/10.1145/1118299.1118371

Published: 24 January 2006 Publication History

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Abstract

Newton is a library-based CAD tool with an analytical synthesis engine which has been developed to support the direct synthesis of the physical design and an electromechanically equivalent model of RF-MEMS resonators based on process parameters and performance metrics. Newton provides accuracy comparable to finite element analysis while requiring a fraction of the computation and design time. A comparison of results from synthesis with Newton, design with FEA, and test results from fabricated devices is presented.

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Cited By

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Van Caekenberghe K(2012)Modeling RF MEMS DevicesIEEE Microwave Magazine10.1109/MMM.2011.217398413:1(83-110)Online publication date: Jan-2012
https://doi.org/10.1109/MMM.2011.2173984

Index Terms

Newton: a library-based analytical synthesis tool for RF-MEMS resonators
1. Hardware
  1. Electronic design automation
    1. High-level and register-transfer level synthesis
    2. Physical design (EDA)
  2. Hardware validation
2. Mathematics of computing
  1. Mathematical analysis
    1. Numerical analysis
      1. Computations in finite fields

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Information & Contributors

Information

Published In

ASP-DAC '06: Proceedings of the 2006 Asia and South Pacific Design Automation Conference

January 2006

998 pages

ISBN:0780394518

General Chair:
Fumiyasu Hirose
Cadence Design Systems, Japan

Publisher

IEEE Press

Publication History

Published: 24 January 2006

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Cited By

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Van Caekenberghe K(2012)Modeling RF MEMS DevicesIEEE Microwave Magazine10.1109/MMM.2011.217398413:1(83-110)Online publication date: Jan-2012
https://doi.org/10.1109/MMM.2011.2173984

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Semismooth Karush-Kuhn-Tucker Equations and Convergence Analysis of Newton and Quasi-Newton Methods for Solving these Equations

Superlinearly convergent approximate Newton methods for LC1 optimization problems

Descent Directions of Quasi-Newton Methods for Symmetric Nonlinear Equations