Analysis of Nonlinear Time Series by Bispectrum Methods and its Applications 


Vol. 6,  No. 5, pp. 1312-1322, May  1999
10.3745/KIPSTE.1999.6.5.1312


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  Abstract

The world of linearity, which is regular, predictable and irrelevant to time sequence in most natural phenomenon, is a very small part. In fact, signals generated from natural phenomenon with which we're in contact are showed only slight linearity. Therefore it is very difficult to understand and analyze natural phenomenon with only predictable and regular linear systems. Due to these reasons researches concerning non-linear signals that of analysis were excluded being regarded as noise are being actively carried out. Countless signals generated from nonlinear system have the information about itself, and analyzing those signals are not simple as in the case of linear system. However, if we find the regularity fixed-quantizing these signals and get information from it, that will be able to be used effectively in so many fields. Hence, in this paper we used a higher order spectrum, especially the bispectrum. After we prove the validity applying bispectrum to logistic map, which is typical chaotic signal. Subsequently by showing the result applying for actual signal analysis of EEG according to auditory stimuli, we show that higher order spectra is a very useful parameter in analysis of non-linear signals and the result of EEG anaylsis according to auditory stimuli.

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[IEEE Style]

K. E. Soo and L. Y. Jung, "Analysis of Nonlinear Time Series by Bispectrum Methods and its Applications," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 6, no. 5, pp. 1312-1322, 1999. DOI: 10.3745/KIPSTE.1999.6.5.1312.

[ACM Style]

Kim Eung Soo and Lee You Jung. 1999. Analysis of Nonlinear Time Series by Bispectrum Methods and its Applications. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 6, 5, (1999), 1312-1322. DOI: 10.3745/KIPSTE.1999.6.5.1312.

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