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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Balli, T. Palaniappan, R. |
| Copyright Year | 2008 |
| Description | Author affiliation: Dept. of Comput. & Electron. Syst., Univ. of Essex, Colchester (Balli, T.; Palaniappan, R.) |
| Abstract | This paper proposes the use of exponential autoregressive (EAR) model for modelling of time series that are known to exhibit non-linear dynamics such as random fluctuations of amplitude and frequency. Biological signal (bio-signal) such as electroencephalogram (EEG) is known to exhibit nonlinear dynamics. Such signals cannot be modelled with traditional linear modelling techniques like autoregressive (AR) models as these models are known to provide only an approximation to the underlying properties of the non-linear signals. In this study, the suitability of EAR models as compared to AR models is shown using EEG signals in addition to several non-linear benchmark time series data where improved signal to noise ratio (SNR) values are indicated by the EAR models. Overall, the results indicate that use of EAR modelling which has yet to be exploited for bio-signal time series analysis has the huge potential in the characterisation and classification of EEG signals. |
| Starting Page | 000485 |
| Ending Page | 000488 |
| File Size | 497837 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424416424 |
| ISSN | 08407789 |
| DOI | 10.1109/CCECE.2008.4564581 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-05-04 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Electroencephalography Time series analysis Brain modeling Ear Biological system modeling Fluctuations Signal to noise ratio Frequency Signal analysis Genetic algorithms Genetic algorithm Exponential autoregressive Electroencephalogram Non-linear time series analysis |
| Content Type | Text |
| Resource Type | Article |
| Subject | Electrical and Electronic Engineering Hardware and Architecture |
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