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A Novel Hybrid Voter Using Genetic Algorithm and Performance History
AKHILESH PATHAK, Anand Mohan
Pages - 117 - 125     |    Revised - 01-07-2011     |    Published - 05-08-2011
Volume - 2   Issue - 3    |    Publication Date - July / August 2011  Table of Contents
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KEYWORDS
TMR, Soft threshold, Genetic Algorithm, Weighted Average Voting
ABSTRACT
Triple Modular Redundancy (TMR) is generally used to increase the reliability of real time systems where three similar modules are used in parallel and the final output is arrived at using voting methods. Numerous majority voting techniques have been proposed in literature however their performances are compromised for some typical set of module output value. Here we propose a new voting scheme for analog systems retaining the advantages of previous reported schemes and reduce the disadvantages associated with them. The scheme utilizes a genetic algorithm and previous performances history of the modules to calculate the final output. The scheme has been simulated using MATLAB and the performance of the voter has been compared with that of fuzzy voter proposed by Shabgahi et al [4]. The performance of the voter proposed here is better than the existing voters.
CITED BY (3)  
1 Pathak, A., Agarwal, T., & Mohan, A. (2015). A Novel Fuzzy Membership Partitioning for Improved Voting in Fault Tolerant System. Journal of Intelligent Learning Systems and Applications, 7(01), 1.
2 Mirsaeidi, M., & Karimi, A. (2015). A novel probabilistic bit voter using genetic algorithm for fault-tolerant systems. International Journal of Computer Science Issues (IJCSI), 12(4), 88.
3 Latifi, Z., & Karimi, A. (2014). A TMR Genetic Voting Algorithm for Fault-tolerant Medical Robot. Procedia Computer Science, 42, 301-307.
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Mr. AKHILESH PATHAK
CEMILAC - India
pathak.akhilesh@gmail.com
Professor Anand Mohan
Department of Electronics Engineering - India