A novel methodology for statistical parameter extraction
ICCAD '95 Proceedings of the 1995 IEEE/ACM international conference on Computer-aided design
Use of sensitivities and generalized substrate models in mixed-signal IC design
DAC '96 Proceedings of the 33rd annual Design Automation Conference
Manufacturability of low power CMOS technology solutions
ISLPED '96 Proceedings of the 1996 international symposium on Low power electronics and design
Layout Dependent Matching Analysis of CMOS Circuits
Analog Integrated Circuits and Signal Processing - Analog circuit techniques and related topics
Current Mirror Layout Strategies for Enhancing Matching Performance
Analog Integrated Circuits and Signal Processing - Special issue on the 1998 and 1999 midwest symposia on circuits and systems
A statistical gate delay model for intra-chip and inter-chip variabilities
ASP-DAC '03 Proceedings of the 2003 Asia and South Pacific Design Automation Conference
New layout strategies with improved matching performance
Analog Integrated Circuits and Signal Processing
Hard-Fault Detection and Diagnosis During the Application of Model-Based Data Converter Testing
Journal of Electronic Testing: Theory and Applications
A perfect matching layout for multiple cascode current sources
CONTROL'05 Proceedings of the 2005 WSEAS international conference on Dynamical systems and control
Proceedings of the 48th Design Automation Conference
Proceedings of the International Conference on Computer-Aided Design
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This paper presents a new methodology for measuring MOS transistor current mismatch and a new transistor current mismatch model. The new methodology is based on extracting the mismatch information from a fully functional circuit rather than on probing individual devices; this extraction leads to more efficient and more accurate mismatch measurement. The new model characterizes the total mismatch as a sum of two components, one systematic and the other random. For our process, we attribute nearly half of the mismatch to the systematic component, which we model as a linear gradient across the die. Furthermore, we present a new model for the random component of the mismatch which is 60% more accurate, on average, than existing models.