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  • In Jour Smart Sensing And Intelligent Systems

 

Research Article

FEATURES OF SLEEP APNEA RECOGNITION AND ANALYSIS

Sleep apnea is a growing sleep disorder issue and estimate to affect 7% of the adult population in Malaysia. In this study, the electrical activity of the brain is studied using Electroencephalogram (EEG). The data obtained was then decomposed using three methods; Empirical Mode Decomposition (EMD), Bivariate EMD and finally Ensemble EMD. The Index of Orthogonatility (IO) was obtained which shows EMD performed the most poorly, EEMD the best and Bivariate in between. The performance of EMD

LEONG WAI YIE, JOEL THAN CHIA MING

International Journal on Smart Sensing and Intelligent Systems , ISSUE 2, 481–497

Article

EMPIRICAL MODE DECOMPOSITION AND ROUGH SET ATTRIBUTE REDUCTION FOR ULTRASONIC FLAW SIGNAL CLASSIFICATION

Feature extraction and selection are the most important techniques for ultrasonic flaw signal classification. In this study, empirical mode decomposition (EMD) is first used to obtain the intrinsic mode functions (IMFs) of original ultrasonic signals. Such IMFs and traditional time as well as frequency domain based statistical parameters are extracted as the initial features of flaw signal. After that, spectral clustering method is used for feature value discretization so that rough set

Yu Wang

International Journal on Smart Sensing and Intelligent Systems , ISSUE 3, 1401–1420

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