| [1] Shoeb A, Edwards H, Connolly J et al. Patient-specificseizure onset detection. Epilepsy & Behavior, 2004, 5(4): 483-498.[2] Febrero M, Galeano P, González-Manteiga W. A functionalanalysis of NOx levels: Location and scale estimation andoutlier detection. Computational Statistics, 2007, 22(3): 411-427.[3] van Wijk J, Van Selow E. Cluster and calendar based visual-ization of time series data. In Proc. the 1999 IEEE Sympo-sium on Information Visualization, Oct. 1999, pp.4-9.[4] Rebbapragada U, Protopapas P, Brodley C, Alcock C. Find-ing anomalous periodic time series. Machine learning, 2009,74(3): 281-313.[5] Rousseeuw P, Leroy A. Robust Regression and Outlier Detec-tion. Wiley Online Library, 1987.[6] Dasgupta D, Forrest S. Novelty detection in time series datausing ideas from immunology. In Proc. the InternationalConference on Intelligent Systems, Dec. 1996, pp.82-87.[7] Hyndman R, Ullah S. Robust forecasting of mortality andfertility rates: A functional data approach. ComputationalStatistics & Data Analysis, 2007, 51(10): 4942-4956.[8] Febrero M, Galeano P, González-Manteiga W. Outlier detec-tion in functional data by depth measures, with application toidentify abnormal NOX levels. Environmetrics, 2008, 19(4):331-345.[9] Keogh E, Lin J, Fu A. HOT SAX: Efficiently finding the mostunusual time series subsequence. In Proc. the 5th IEEE In-ternational Conference on Data Mining, Nov. 2005, pp.226-233.[10] Lin J, Keogh E, Fu A, Van Herle H. Approximations to magic:Finding unusual medical time series. In Proc. the 18th IEEESymposium on Computer-Based Medical Systems, Jun. 2005,pp.329-334.[11] Bu Y, Leung T, Fu A, Keogh E, Pei J, Meshkin S. WAT:Finding top-K discords in time series database. In Proc. the7th SIAM International Conference on Data Mining, Apr.2007.[12] Yankov D, Keogh E, Rebbapragada U. Disk aware discord dis-covery: Finding unusual time series in terabyte sized datasets.Knowledge and Information Systems, 2008, 17(2): 241-262.[13] Goldberger A, Amaral L, Glass L et al. Physiobank, phys-iotoolkit, and physionet: Components of a new research re-source for complex physiologic signals. Circulation, 2000,101(23): e215-e220.[14] Shoeb A, Guttag J. Application of machine learning to epilep-tic seizure detection. In Proc. the 27th International Confer-ence on Machine Learning, Jun. 2010, pp.975-982.[15] Pham N, Le Q, Dang T. HOT aSAX: A novel adaptive sym-bolic representation for time series discords discovery. InProc. the 2nd Intelligent Information and Database Systems,Mar. 2010, pp.113-121.[16] Fu A, Leung O, Keogh E, Lin J. Finding time series discordsbased on Haar transform. In Proc. the 2nd Advanced DataMining and Applications, Aug. 2006, pp.31-41.[17] Shieh J, Keogh E. iSAX: Indexing and mining terabyte sizedtime series. In Proc. the 14th ACM SIGKDD InternationalConference on Knowledge Discovery and Data Mining, Aug.2008, pp.623-631.[18] Son M, Anh D. EWAT+: Finding time series discords basedon new discord measure functions. In Proc. IEEE Inter-national Conference on Computing & Communication Tech-nologies, Research, Innovation, and Vision for the Future,Nov. 2010, pp.1-4.[19] Luo W, Gallagher M. Faster and parameter-free discordsearch in quasi-periodic time series. In Proc. PAKDD, May2011, pp.135-148.[20] Eckmann J, Kamphorst S, Ruelle D. Recurrence plots of dy-namical systems. Europhysics Letters, 1987, 4(9): 973-977.[21] Iwanski J, Bradley E. Recurrence plots of experimental data:To embed or not to embed? Chaos: An InterdisciplinaryJournal of Nonlinear Science, 1998, 8(4): 861-871.[22] Webber Jr C, Zbilut J. Recurrence quantification analysisof nonlinear dynamical systems. Tutorials in ContemporaryNonlinear Methods for the Behavioral Sciences, 2005, pp.26-94.[23] Marwan N, Carmen Romano M C, Thiel M, Kurths J. Re-currence plots for the analysis of complex systems. PhysicsReports, 2007, 438(5/6): 237-329.[24] Marwan N. A historical review of recurrence plots. The Eu-ropean Physical Journal-Special Topics, 2008, 164(1): 3-12.[25] Chatfield C. The Analysis of Time Series: An Introduction,(6th edition). Chapman & Hall/CRC, 2004.[26] Keogh E, Lin J, Fu A. The UCR time series discords.http://www.cs.ucr.edu/~eamonn/discords/, April 2010.[27] Hyndman R. Time series data library. http://data.is/TSDLde-mo, April 2010. |