• DocumentCode
    3400843
  • Title

    Automatic stationary detection of time series using auto-correlation coefficients and LVQ — Neural network

  • Author

    Poulos, Marios ; Papavlasopoulos, Sozon

  • Author_Institution
    Lab. of Inf. Technol., Ionian Univ., Corfu, Greece
  • fYear
    2013
  • fDate
    10-12 July 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A data mining of Time Series using Autocorrelation Coefficients (ACC) and LVQ -Neural Network is addressed in this work-a problem that has not yet been seen in a signal processing framework, to the best of our knowledge. Neural network classification was performed on real Time series Data of real data, in an attempt to experimentally investigate the connection between Time Series data and hidden information about the properties of stationary Time Series. Finally, the ability of the ACC will be tested via a well fitted LVQ neural network which gives satisfactory results in predicting Time Series.
  • Keywords
    data mining; neural nets; time series; LVQ neural network; autocorrelation coefficients; automatic stationary detection; data mining; neural network classification; signal processing framework; time series data; Electroencephalography; Equations; Neural networks; Neurons; Support vector machine classification; Time series analysis; Vectors; Auto Corellation Coefficients; Data Mining; LVQ Neural Network; Stationarity; Time Series;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information, Intelligence, Systems and Applications (IISA), 2013 Fourth International Conference on
  • Conference_Location
    Piraeus
  • Print_ISBN
    978-1-4799-0770-0
  • Type

    conf

  • DOI
    10.1109/IISA.2013.6623678
  • Filename
    6623678