DocumentCode
2226513
Title
Monte Carlo analysis of resistive networks without a priori probability distributions
Author
Barmish, B. Ross ; Kettani, Houssain
Author_Institution
Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA
Volume
3
fYear
2000
fDate
2000
Firstpage
263
Abstract
In this paper, we formulate and solve a new type of Monte Carlo problem for a resistive network. Given lower and upper bounds on the value of each resistor but no probability distribution, we consider the problem of finding the expected value for a designated gain. In view of the fact that no a priori probability distributions for the uncertain resistors are assumed, a certain type “distributional robustness” is sought. To this end, a new paradigm from the robustness literature is particularized to circuits and results are provided in this context. Some of the performance bounds obtained via this new approach differ considerably from those which result from a more conventional Monte Carlo simulation
Keywords
Monte Carlo methods; linear network analysis; lumped parameter networks; passive networks; Monte Carlo analysis; designated gain; distributional robustness; expected value; resistive networks; uncertain resistors; Circuits; Monte Carlo methods; Probability density function; Probability distribution; Resistors; Robustness; Uncertainty; Upper bound; Voltage; Writing;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2000. Proceedings. ISCAS 2000 Geneva. The 2000 IEEE International Symposium on
Conference_Location
Geneva
Print_ISBN
0-7803-5482-6
Type
conf
DOI
10.1109/ISCAS.2000.856047
Filename
856047
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