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Srinivasan Rajaraman, Ph.D. - Publications

Affiliations: 
2006 Texas A & M University, College Station, TX, United States 
Area:
Chemical Engineering
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7 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2009 Rajaraman S, Gribok AV, Wesensten NJ, Balkin TJ, Reifman J. An improved methodology for individualized performance prediction of sleep-deprived individuals with the two-process model. Sleep. 32: 1377-92. PMID 19848366 DOI: 10.1093/Sleep/32.10.1377  0.328
2008 Rajaraman S, Gribok AV, Wesensten NJ, Balkin TJ, Reifman J. Individualized performance prediction of sleep-deprived individuals with the two-process model. Journal of Applied Physiology (Bethesda, Md. : 1985). 104: 459-68. PMID 18079260 DOI: 10.1152/Japplphysiol.00877.2007  0.346
2007 Reifman J, Rajaraman S, Gribok AV. Moving towards individualized performance models. Sleep. 30: 1081-2; discussion 1. PMID 17910378 DOI: 10.1093/Sleep/30.9.1081  0.331
2006 Rajaraman S, Hahn J, Mannan MS. Sensor fault diagnosis for nonlinear processes with parametric uncertainties. Journal of Hazardous Materials. 130: 1-8. PMID 16298476 DOI: 10.1016/J.Jhazmat.2005.07.037  0.546
2006 Rajaraman S, Kruger U, Mannan MS, Hahn J. A new sensor fault diagnosis technique based upon subspace identification and residual filtering Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 4114: 990-998.  0.504
2004 Rajaraman S, Hahn J, Mannan MS. A methodology for fault detection, isolation, and identification for nonlinear processes with parametric uncertainties Industrial & Engineering Chemistry Research. 43: 6774-6786. DOI: 10.1021/Ie0400806  0.637
2004 Rajaraman S, Hahn J, Mannan MS. A methodology for fault detection, isolation, and identification for nonlinear processes with parametric uncertainties Industrial and Engineering Chemistry Research. 43: 6774-6786.  0.607
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