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Theoretical Basis of Novelty Detection in Time Series Using Negative Selection Algorithms

  • Rafał Pasek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4163)

Abstract

Theoretical basis of Novelty Detection in Time Series and its relationships with State Space Reconstruction are discussed. It is shown that the methods for estimation of optimal state-space reconstruction parameters may be used for the estimation of immunological novelty detection system’s parameters. This is illustrated with a V-detector system detecting novelties in Mackey-Glass time series.

Keywords

Anomaly Detection Window Length Artificial Immune System Novelty Detection Chaotic Time Series 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Rafał Pasek
    • 1
  1. 1.Wrocław University of TechnologyWrocławPoland

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