Hierarchical statistical analysis of performance variation for continuous-time delta-sigma modulators

Author

Tang, Hua

Author_Institution

Electrical and Computer Engineering Department University of Minnesota Duluth, 55812 37, USA

fYear

2007

fDate

15-17 Oct. 2007

Firstpage

37

Lastpage

41

Abstract

Statistical analysis has become increasingly important with increasing process parameter variations in manufacturing. Monte Carlo method has been most popular for statistical analysis, but it is not efficient for complex circuits/systems due to overwhelming computational time. In this paper, we present a general hierarchical method for efficient statistical analysis of performance parameter variations for complex circuits/systems and conduct a case study on a 4th order continuous-time Delta Sigma modulator. At circuit-level, we use response surface modeling method to extract quadratic models of circuit- level performance parameters in terms of process parameter variations. Then, at system-level, we use behavioral models to extract statistical distribution of the overall system performance parameter. The method can achieve a good tradeoff between computational efficiency and accuracy.

Keywords

Analytical models; Circuit analysis computing; Circuit simulation; Computational modeling; Computer aided manufacturing; Delta modulation; Manufacturing processes; Response surface methodology; Statistical analysis; Statistical distributions; Delta-Sigma modulator; behavioral modeling; process variation; response surface modeling; statistical analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Very Large Scale Integration, 2007. VLSI - SoC 2007. IFIP International Conference on

Conference_Location

Atlanta, GA, USA

Print_ISBN

978-1-4244-1710-0

Electronic_ISBN

978-1-4244-1710-0

Type

conf

DOI

10.1109/VLSISOC.2007.4402469

Filename

4402469