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
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;
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
DOI :
10.1109/ISCAS.2000.856047