Cart (Loading....) | Create Account
Close category search window

An efficient statistical analysis methodology and its application to high-density DRAMs

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Sang-Hoon Lee ; Semicond. R&D Center, Samsung Electron. Co. Ltd., Kyungki-Do, South Korea ; Chang-Hoon Choi ; Jeong-Taek Kong ; Won-Seong Lee
more authors

A new approach for the statistical worst case of fall-chip circuit performance and parametric yield prediction, using both the modified-principal component analysis (MPCA) and the gradient method (GM), is proposed and verified. This method enables designers not only to predict the standard deviations of circuit performances but also track the circuit performances associated with the process shift using wafer test structure measurements. This new method is validated experimentally during the development and production of high density DRAMs.

Published in:

Computer-Aided Design, 1997. Digest of Technical Papers., 1997 IEEE/ACM International Conference on

Date of Conference:

9-13 Nov. 1997

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.