Ensemble empirical mode decomposition (EEMD) is a noise-assisted data analysis method which decomposes a signal into a collection of intrinsic mode functions (IMFs). There nevertheless appears a multi-mode problem where signals with a similar timescale are decomposed into different IMF components. A possible solution to this problem is to recombine the multi-mode IMF components into a proper si...

Article history: Received 27 September 2016 Received in revised form 25 May 2017 Accepted 22 November 2017 Available online 5 December 2017

The concepts of intrinsic mode functions and mono-components are investigated in relation to the empirical mode decomposition. Mono-components are defined to be the functions for which non-negative analytic instantaneous frequency is well defined. We show that a great variety of functions are mono-components based on which adaptive decomposition of signals are theoretically possible. We justify...

Article history: Iris recognition is known Received 5 December 2006 Received in revised form 31 July 2008 Accepted 28 September 2008 Available online 26 October 2008

This paper describe the features extraction algorithm for electrocardiogram (ECG) signal using Huang Hilbert Transform and Wavelet Transform. ECG signal for an individual human being is different due to unique heart structure. The purpose of feature extraction of ECG signal would allow successful abnormality detection and efficient prognosis due to heart disorder. Some major important features ...