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A Holistic Approach to Distributed Dimensionality Reduction of Big Data

2.28 out of 5 based on 36 customer ratings
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Categories: 2016 Projects, NS2, Wireless Sensor Networking, 2015 Projects, Final Year Projects Tags: academic projects, Android project 2013-2014, Android project 2015-2016, Android project Abstract, Android project list, btech projects, dotnet project 2013-2014, dotnet project 2015-2016, dotnet project Abstract, dotnet project list, elysium technologies abstract, elysium technologies chennai, elysium technologies coimbatore, elysium technologies company, elysium technologies courses, elysium technologies erode, elysium technologies inpant traning, elysium technologies internship, elysium technologies jobs, elysium technologies madurai, elysium technologies mou, elysium technologies pondychery, elysium technologies projectlist, elysium technologies projects, elysium technologies ramnad, elysium technologies salem, elysium technologies software, elysium technologies tirunelveli, elysium technologies trichy, Final Year Projects, java projects 2013-2014, java projects 2015-2016, java projects Abstract, madurai software company, matlab project 2013-2014, matlab project 2015-2016, matlab project Abstract, matlab project list, mtech projects, phd research work, Php project 2013-2014, Php project 2015-2016, Php project Abstract, Php project list, Power Electronic project 2013-2014, Power Electronic project 2015-2016, Power Electronic project Abstract, Power Electronic project list, project center Bangalore, project center chennai, project center coimbatore, project center Erode, project center Hyderabad, project center Kollam, project center madurai, project center Pandicherry, project center ramnad, project center Salem, project center Tiruneveli, project center trichy, research center, Students Projects, Vlsi project 2013-2014, Vlsi project 2015-2016, Vlsi project Abstract, Vlsi project list
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A Holistic Approach to Distributed Dimensionality Reduction of Big Data

Abstract— Advances in CMOS technology have made digital circuits and systems very sensitive to manufacturing variations, aging, and/or soft errors. Fault-tolerant techniques using hardware redundancy have been extensively investigated for improving reliability. Quadded logic (QL) is an interwoven redundant logic technique that corrects errors by switching them from critical to subcritical status; however, QL cannot correct errors in the last one or two layers of a circuit. In contrast to QL, quadded transistor (QT) corrects errors while performing the function < Final Year Projects 2016 >of a circuit. A technique that combines QL with QT is proposed to take advantage of both techniques. The proposed quadded logic with quadded transistor (QLQT) technique is evaluated and compared with other fault-tolerant techniques, such as triple modular redundancy and triple interwoven redundancy, using stochastic computational models. Simulation results show that QLQT has a better reliability than the other fault-tolerant techniques (except in the very restrictive case of small circuits with low gate error rates and very short paths from primary inputs to primary outputs). These results provide a new insight for implementing efficient fault-tolerant techniques in the design of reliable circuits and systems.

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Rated 2.28 out of 5 stars
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