TY - GEN
T1 - Hierarchical statistical analysis of performance variation for continuous-time delta-sigma modulators
AU - Tang, Hua
PY - 2007
Y1 - 2007
N2 - 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.
AB - 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.
KW - Behavioral modeling
KW - Delta-Sigma modulator
KW - Process variation
KW - Response surface modeling
KW - Statistical analysis
UR - http://www.scopus.com/inward/record.url?scp=50149117252&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=50149117252&partnerID=8YFLogxK
U2 - 10.1109/VLSISOC.2007.4402469
DO - 10.1109/VLSISOC.2007.4402469
M3 - Conference contribution
AN - SCOPUS:50149117252
SN - 9781424417100
T3 - 2007 IFIP International Conference on Very Large Scale Integration, VLSI-SoC
SP - 37
EP - 41
BT - 2007 IFIP International Conference on Very Large Scale Integration, VLSI-SoC
T2 - 2007 IFIP International Conference on Very Large Scale Integration, VLSI-SoC
Y2 - 15 October 2007 through 17 October 2007
ER -