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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Mehran, Y.Z. Nasrabadi, A.M. |
| Copyright Year | 2008 |
| Description | Author affiliation: Bioelectric Group & Young Researchers Club Member, Islamic Azad Univ., Tehran (Mehran, Y.Z.) || Amirkabir Univ. of Technol., Tehran (Nasrabadi, A.M.) |
| Abstract | There is growing interest in modeling and processing nonlinear behavior in the biological systems. In this paper we applied such methods for detecting Functional Disorder in Gastric. Conventional tools for analyzing such data use information from the power spectral density of the time series, and hence are restricted to little information of data. This information does not provide a sufficient representation of a signal with strong nonlinear properties. In this work, we attempt to extract various nonlinear dynamical invariants of the underlying attractor from the signals. We show that these invariants can discriminate between normal and Functional Gastrointestinal Disorders (FGD) classes. |
| File Size | 493863 |
| File Format | |
| ISBN | 9781424417391 |
| DOI | 10.1109/IS.2008.4670470 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-09-06 |
| Publisher Place | Bulgaria |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Neural networks Stomach Chaos Biomedical engineering Phase detection Delay Time series analysis Bioelectric phenomena Pathology Couplings Neural Network Strange Attractor Functional Gastric Disorder |
| Content Type | Text |
| Resource Type | Article |
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