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|Title:||Stochastic behavioral modeling and analysis for analog/mixed-signal circuits||Authors:||Gong, Fang
|Keywords:||DRNTU::Engineering::Electrical and electronic engineering::Integrated circuits||Issue Date:||2012||Source:||Gong, F., Basir-Kazeruni, S., He, L., & Yu, H. (2013). Stochastic Behavioral Modeling and Analysis for Analog/Mixed-Signal Circuits. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 32(1), 24-33.||Series/Report no.:||IEEE transactions on computer-aided design of integrated circuits and systems||Abstract:||It has become increasingly challenging to model the stochastic behavior of analog/mixed-signal (AMS) circuits under large-scale process variations. In this paper, a novel moment-matching based method has been proposed to accurately extract the probabilistic behavioral distributions of AMS circuits. This method first utilizes Latin Hypercube Sampling (LHS) coupling with a correlation control technique to generate a few samples (e.g., sample-size is in linear with number of variable parameters) and further analytically evaluate the high-order moments of the circuit behavior with high accuracy. In this way, the “arbitrary” probabilistic distributions of the circuit behavior can be extracted using moment-matching method. More importantly, the proposed method has been successfully applied to high-dimensional prob-lems with linear complexity. The experiments demonstrate that the proposed method can provide up to 1666X speedup over crude Monte Carlo method for the same accuracy.||URI:||https://hdl.handle.net/10356/95295
|ISSN:||0278-0070||DOI:||http://dx.doi.org/10.1109/TCAD.2012.2217961||Rights:||© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/TCAD.2012.2217961].||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Journal Articles|
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