A Novel 20G Wide-Band Synthesis Methodology for CMOS Spiral Inductors using Neural Network and Genetic Algorithm

DOI

10.2991/iske.2007.221How to use a DOI?

Keywords

CMOS spiral inductor, neural network, genetic algorithm, layout parameter optimization.

Abstract

We develop a novel synthesis way to effectively generate CMOS spiral inductor’s layout parameters using artificial neural network and genetic algorithm. An accurate neural network model for CMOS spiral inductors is firstly developed based on measured results from TSMC 0.13um MM/RF process with the frequency range of 1-20 GHz. The neural network model is further integrated in the synthesis simulator kits called SPUNK. An innovative synthesis technique is then applied in which genetic algorithm based optimization is adopted. Our methodology promises to provide greater accuracy than previous results in the frequency range while able to minimize the time cost for spiral inductor design.

Copyright

© 2007, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Haiyang Shen
AU  - Wenjun Zhang
PY  - 2007/10
DA  - 2007/10
TI  - A Novel 20G Wide-Band Synthesis Methodology for CMOS Spiral Inductors using Neural Network and Genetic Algorithm
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 1298
EP  - 1302
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.221
DO  - 10.2991/iske.2007.221
ID  - Shen2007/10
ER  -