Use of chaotic modeling for transmission of EEG data

Author

Kavitha, V. ; Dutt, D. Narayana

Author_Institution

Dept. of Electr. Commun. Eng., Indian Inst. of Sci., Bangalore, India

Volume

3

fYear

1997

fDate

9-12 Sep 1997

Firstpage

1262

Abstract

A method based on chaotic modeling for compression and transmission of EEG data is presented. It is assumed that the data to be transmitted is chaotic and is generated by an E-dimensional nonlinear system. The flow in the E-dimensional space is obtained from the one dimensional time series using the process of time delay embedding. Then a simple, linear model is fitted for this flow in the E-dimensional space and this model is used as a predictor in the general DPCM scheme for transmission. Since this model was able to give very good one-step prediction, we were able to achieve a reduction of about 50 percent of the dynamic range of the signal to be transmitted (and hence a reduction in bit rate also). A further advantage is that this is achieved with the additional feature of reduced complexity when compared to the conventionally used AR model

Keywords

bandwidth compression; chaos; data compression; delays; differential pulse code modulation; electroencephalography; medical signal processing; nonlinear systems; prediction theory; time series; AR model; DPCM; E-dimensional space; EEG data transmission; bandwidth reduction; bit rate reduction; chaotic modeling; data compression; dynamic range reduction; linear model; nonlinear system; one dimensional time series; one-step prediction; predictor; reduced complexity; time delay embedding; Bandwidth; Bit rate; Brain modeling; Chaos; Chaotic communication; Data engineering; Delay effects; Electroencephalography; Nonlinear systems; Predictive models;

fLanguage

English

Publisher

ieee

Conference_Titel

Information, Communications and Signal Processing, 1997. ICICS., Proceedings of 1997 International Conference on

Print_ISBN

0-7803-3676-3

Type

conf

DOI

10.1109/ICICS.1997.652189

Filename

652189