References
[1]. Z. Georgiev, M. Stojcev (1994). VLSI common voting module for fault-tolerant TMR system in industrial system control applications, Internat. J. Electron. 76 (2) 163–205.
[2]. B.W. Johnson (1989). Design and Analysis of Fault-Tolerant Digital Systems, Addison Wesley, Reading, MA.
[3]. M.K. Stojcev, J.Lj. Djordgevic, M.D. Krstic (2001). A hardware mid-value select voter architecture, Microelectron. J. 32 149–162.
[4]. J.M. Bass, P.R. Croll, P.J. Fleming, L.J.C. Woolliscroft (1994). Three domain voting in real-time distributed control systems, Proc. 2nd Euromicro Workshop on Parallel and Distributed Processing, pp. 317–324.
[5]. K. Kim, M.A. Vouk, D.E. McAllister (1996). An empirical evaluation of maximum likelihood voting in failure correlation conditions, Proc. ISSRE'96 pp. 330–339.
[6]. K. Kim, M.A. Vouk, D.F. McAllister (1998). Fault tolerant software voters based on fuzzy equivalence relations, Proc. IEEE Aerospace Conf. 4 ,pp. 5–19.
[7]. G. Latif-Shabgahi (1999). Performance analysis of software implemented inexact voting algorithms, Ph.D. Thesis, Department of Automatic Control and Systems Engineering, The University of SheKeld, SheKeld, UK.
[8]. G. Latif-Shabgahi, J.M. Bass, S. Bennett (1998). Complete disagreement in redundant real-time control applications, Proc.5th IFAC Workshop on Algorithms and Architectures for Real-Time Control, Cancun, Mexico, April 15–17,pp. 259–264.
[9]. P.R. Lorczak, A.K. Caglayan & D.E. Eckhardt (1989). A Theoretical Investigation of Generalized Voters for Redundant Systems, presented at FTCS-19. Digest of Papers, Nineteenth International Symposium on Fault-Tolerant Computing, Chicago, USA.
[10]. M. Tagvaei (2001). Experimental evaluation of voting algorithms, M.Sc. Thesis, Automatic Control and Systems Department, The University of SheKeld, SheKeld, UK.
[11]. A.D. De Leon (2003). Voting algorithms, M.Sc. Thesis, Department of Automatic Control and Systems Engineering Department, The University of SheKeld, SheKeld, UK.
[12]. G. Latif-Shabgahi & A.J. Hirst, (2005). A fuzzy voting scheme for hardware and software fault tolerant systems, Fuzzy Sets and Systems, 150 (3) 579–598.
[13]. R. Hoseinnezhad & A. Bab-Hadiashar (2006). Fusion of redundant information in brake-by- wire systems using a fuzzy voter. Journal of Advances in Information Fusion,1(1):pp. 52–62.
[14]. S. Blank, T. Fohst, & K. Berns (2010). “A fuzzy approach to low level sensor fusion with limited system knowledge,” in 13th International Conference on Information Fusion, Edinburgh, Scottland.
[15]. J.-C. Laprie, (1985). Dependable computing and fault-tolerance: concepts and terminology, in Digest of Papers FTCS'15: IEEE 15th Annu. Int.Symp. Fault-Tolerant Computing Systems, Ann. Arbor, MI, pp. 2–11.
[16]. L. Chen & A. Avizienis (1978). N-Version Programming: a fault-tolerance approach to reliability of software operation, in Digest of Papers FTCS'8: IEEE 8th Annu. Int. Symp. Fault-Tolerant Computing Systems, Toulouse, France, June 1978, pp. 3–9.
[17]. D.M. Blough & G.F. Sullivan (1990). A comparison of voting strategies for fault-tolerant distributed systems, in Proc. IEEE 9th Symp. Reliable Distributed Systems, Huntsville, Alabama, pp. 136–145.
[18]. G. Latif-Shabgahi (2004). A Novel Algorithm for Weighted Average Voting Used in Fault-Tolerant Computing Systems, Microprocessors and Microsystems, Vol. 28, pp. 357-361.
[19]. G. Latif-Shabgahi, J.M. Bass, & S. Bennett (2001). History-Based Weighted Average Voter: A Novel Software Voting Algorithm for Fault-Tolerant Computer Systems, Euromicro Conference on Parallel, Distributed, and Network-Based Processing, pp. 402-409.
[20]. G. Latif-Shabgahi, Julian M. Bass & Stuart Bennett (2004). A taxonomy for software voting algorithms used in safety-critical systems, IEEE Trans. Reliability, vol. 53, no. 3, pp 319-328.
[21]. G. Latif-Shabgahi & S. Bennett (1999). Adaptive majority voter: a novel voting algorithm for real-time fault-tolerant control systems, in 25th Euromicro Conf., vol. 2, pp. 113-120.
[22]. S. Phani Kumar, P.S.Ramaiah & V.Khanaa (2011). Architectural Patterns to Design Software Safety based Safety-Critical Systems, Proceedings of ICCCS' 11 International Conference on Communication, Computing & Security, pp:620-623 ACM New York, NY, USA ©2011 ISBN: 978-1-4503-0464-1 doi>10.1145/1947940.1948069.
[23]. M. Das, & S. Battacharya (2010). A Modified History Based Weighted Average Voting with Soft-Dynamic Threshold, in ACE '10, International Conference on Advances in Computer Engineering, ISBN: 978-0-7695-4058-0 doi>10.1109/ACE.2010.45.
[24]. Zarafshan, F, Latif-Shabgahi & G.R., Karimi (2010). “A Novel Weighted Voting algorithm based on Neural Networks for Fault-Tolerance Systems”, ICCSIT, IEEE International Conference on Computer Science and Information Technology, pp.135-139 doi>10.1109/ICCSIT.2010. 5565122.
[25]. PhaniKumar Singamsetty & Seetha Ramaiah Panchumarthy (2011). A Novel History based Weighted Voting Algorithm for Safety Critical Systems, Special Issue on Advanced Algorithms in Journal of Advances in Information Technology, ISSN 1798-2340. Vol. 2, Issue 3, pp.139 – 145.