A study of increasing the speed of the Independent Component Analysis (ICA) using wavelet technique

Koredianto Usman*, Hiroshi Juzoji, Isao Nakajima, Muhammad Athar Sadiq

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

Independent Component Analysis (ICA) is a multivariate data analysis tool. The basic principle of ICA is the assumption of independency of the source data. On the separation of the data source, ICA algorithm searches for a demixing matrix that will maximize the independency. This searching process is mostly done in iterative way and involving high order statistics. This process is time consuming. For a certain application, such as speech, where the source signal has its power at the lower frequency, we can reduce the data length by removing the high frequency component. Wavelet decomposition is a popular method for this purpose. In this paper, we propose the data reduction using Wavelet as a preprocessing of ICA to speed up the ICA computation. We investigate Haar, Daubechies 2, Daubechies 3, and Daubechies 4 Wavelet as the wavelet analysis. We further investigate the computation time as the function of level of decomposition of the wavelet. In this study, we found that Haar Wavelet at third level of decomposition gave the biggest advantage of computation speed, which is about 40-50%.

Original languageEnglish
Title of host publicationProceedings - 6th International Workshop on Enterprise Networking and Computing in Healthcare Industry, Healthcom 2004
EditorsK. Kurokawa, I. Nakajima, Y. Ishibashi
Pages73-75
Number of pages3
Publication statusPublished - 2004
Externally publishedYes
EventProceedings - 6th International Workshop on Enterprise Networking and Computing in Healthcare Industry, Healthcom 2004 - Odawara, Japan
Duration: Jun 28 2004Jun 29 2004

Publication series

NameProceedings - 6th International Workshop on Enterprise Networking and Computing in Healthcare Industry, Healthcom 2004

Conference

ConferenceProceedings - 6th International Workshop on Enterprise Networking and Computing in Healthcare Industry, Healthcom 2004
Country/TerritoryJapan
CityOdawara
Period6/28/046/29/04

Keywords

  • Decomposition
  • Independent Component Analysis
  • Low Frequency signals
  • Wavelet

ASJC Scopus subject areas

  • Engineering(all)

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