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Permanent link (DOI): https://doi.org/10.7939/R3F30X

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Probabilistic and Stochastic Computational Models: from Nanoelectronic to Biological Applications Open Access

Descriptions

Other title
Subject/Keyword
stochastic computation
probabilistic computation
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Liang, Jinghang
Supervisor and department
Han, Jie (Electrical and Computer Engineering)
Examining committee member and department
Lin, Guohui (Computer Science)
Cockburn, Bruce (Electrical and Computer Engineering)
Han, Jie (Electrical and Computer Engineering)
Department
Department of Electrical and Computer Engineering
Specialization

Date accepted
2012-08-20T13:12:02Z
Graduation date
2012-11
Degree
Master of Science
Degree level
Master's
Abstract
A finite state machine (FSM) is a classical abstract model for sequential circuits that are at the core of any digital system. Due to fabrication defects and transient faults, the reliable operation of sequential circuits is greatly desired. In this thesis, computational models are initially constructed using state transition matrices (STMs) and binary decision diagrams (BDDs) of an FSM; a phenomenon called error masking and the restoring properties of sequential circuits are then analyzed in detail. This analysis provides a basis for further devising efficient and robust implementation when designing FSMs. Arithmetic circuits play an important role in many digital systems and have fundamentally critical applications in signal processing. Addition is perhaps the most important and basic arithmetic operation for many applications. Recent research has focused on probabilistic and approximate adders that trade off accuracy for energy saving. Since there was a lack of appropriate metrics to evaluate the efficacy of these inexact designs, several new metrics are proposed in this work for evaluating the reliability as well as the power efficiency of an adder. These new metrics can be used in future designs for a better assessment of the power and precision tradeoff. Although current digital systems are based on complementary metal–oxide–semiconductor (CMOS) technology and employ binary values in the representation of signals, multiple valued logic (MVL) circuits using novel nano-devices have been investigated due to their advantages in information density and operating speed. In this thesis, pseudo-complementary MVL circuits are further proposed for implementations using carbon nanotube field effect transistors (CNTFETs). Because of the fabrication non-idealities, reliability evaluation of these MVL circuits becomes important. Subsequently, stochastic computational models (SCMs) are developed to analyze the reliability of CNT MVL circuits. Finally, the stochastic computational model is applied in the modeling of biological networks. Specifically, stochastic Boolean networks (SBNs) are proposed for an efficient modeling of genetic regulatory networks (GRNs). The proposed SBN can accurately and efficiently simulate a GRN without and with random gene perturbation, which will help to reveal biologically meaningful insights for a better understanding of the dynamics of GRNs.
Language
English
DOI
doi:10.7939/R3F30X
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
J. Liang, J. Han, "Stochastic Boolean Networks: An Efficient Approach to Modeling Gene Regulatory Networks", Accepted for publication in BMC Systems Biology. (Manuscript ID: 1384557057730389; Accepted on August 6, 2012.).J. Liang, J. Han, F. Lombardi, "Analysis of Error Masking and Restoring Properties of Sequential Circuits", to appear in IEEE Transactions on Computers. (Manuscript ID: TC-2011-10-0762; Accepted on June 2, 2012.).J. Liang, J. Han, F. Lombardi, “New Metrics for the Reliability of Approximate and Probabilistic Adders”, to appear in IEEE Transactions on Computers. (Manuscript ID: TC-2011-12-0946; Accepted on May 28, 2012.).J. Liang, L. Chen, J. Han, F. Lombardi, "Design and Reliability Analysis of Multiple Valued Logic Gates using Carbon Nanotube FETs", IEEE/ACM International Symposium on Nanoscale Architectures, the Netherland, pp. 131-138, 2012.J. Liang, J. Han, F. Lombardi, “On the Reliable Performance of Sequential Adders for Soft Computing”, IEEE international Symposium on Defect and Fault Tolerant in VLSI systems (DFT), Vancouver, BC, Canada, pp. 3-10, 2011.H. Chen, J. Liang, J. Han and F. Lombardi, “A Stochastic Computational Approach for Accurate and Efficient Reliability Evaluation”, IEEE Transactions on Computers. (Manuscript ID: TC-2012-03-0170; Revised and resubmitted on March 4, 2012.).

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