Efficient Hybrid Performance Modeling for Analog Circuits Using Hierarchical Shrinkage Priors


Journal Article

© 2016 IEEE. Efficient performance modeling is an extremely important task for yield analysis and design optimization of analog circuits. In this paper, a novel regression modeling method based on hierarchical shrinkage priors is proposed to construct hybrid performance models with both high accuracy and low computational cost. In particular, the user-defined model templates derived from design equations and the general-purpose orthogonal polynomials are combined together to set up a hybrid dictionary. Next, in order to avoid over-shrinking large model coefficients, a novel regression method based on hierarchical shrinkage priors and variational Bayesian inference is adopted for model fitting. A rail-to-rail operational amplifier example demonstrates that the proposed method achieves up to 40% error reduction over other state-of-the-art approaches without increasing the modeling cost.

Full Text

Duke Authors

Cited Authors

  • Liao, C; Tao, J; Yu, H; Tang, Z; Su, Y; Zhou, D; Zeng, X; Li, X

Published Date

  • December 1, 2016

Published In

Volume / Issue

  • 35 / 12

Start / End Page

  • 2148 - 2152

International Standard Serial Number (ISSN)

  • 0278-0070

Digital Object Identifier (DOI)

  • 10.1109/TCAD.2016.2543021

Citation Source

  • Scopus