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RBF Neural Network for Probability Density Function Estimation and Detecting Changes in Multivariate Processes

  • Ewa Skubalska-Rafajłowicz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4029)

Abstract

We propose a new radial basis function (RBF) neural network for probability density function estimation. This network is used for detecting changes in multivariate processes. The performance of the proposed model is tested in terms of the average run lengths (ARL), i.e., the average time delays of the change detection. The network allows the processing of large streams of data, memorizing only a small part of them. The advantage of the proposed approach is in the short and reliable net training phase.

Keywords

Radial Basis Function Control Chart Radial Basis Function Neural Network Radial Basis Function Network Average Time Delay 
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

  • Ewa Skubalska-Rafajłowicz
    • 1
  1. 1.Institute of Computer EngineeringControl and Robotics, Wrocław University of TechnologyWrocławPoland

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