A New QRS Detection Algorithm Based on Empirical Mode Decomposition

2008 ◽  
Author(s):  
Hongyan Xing ◽  
Minsong Huang
Keyword(s):  
Empirical Mode Decomposition ◽  
Detection Algorithm ◽  
Qrs Detection ◽  
Mode Decomposition

Application of Bidimensional Empirical Mode Decomposition to Medical Liquid Opacity Detection

2011 ◽  
Vol 128-129 ◽  
pp. 530-533
Author(s):  
Jian Wan ◽  
Yuan Peng Diao ◽  
Dong Mei Yan ◽  
Qiang Guo ◽  
Zhen Shen Qu
Keyword(s):  
Edge Detection ◽  
Empirical Mode Decomposition ◽  
External Environment ◽  
Detection Algorithm ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Edge Detection Algorithm ◽  
Mode Decomposition ◽  
Simulation Results ◽  
Bidimensional Empirical Mode Decomposition

A Robert operator edge detection algorithm based on Bidimensional Empirical Mode Decomposition (BEMD) to detect medical liquid opacity is proposed. This method can effectively resolve the problem that traditional Robert operator edge detection can be easily effected by noise, and it also has certain effects on restraining external environment influence. The simulation results show that, compare with traditional medical liquid opacity detection methods, the proposed method could achieve higher detection accuracy, and has a certain theory and application value.

scholarly journals Empirical Mode Decomposition of the Acceleration Response of a Prismatic Beam Subject to a Moving Load to Identify Multiple Damage Locations

2012 ◽  
Vol 19 (5) ◽  
pp. 845-856 ◽  
Author(s):  
J. Meredith ◽  
A. González ◽  
D. Hester
Keyword(s):  
Finite Element ◽  
Empirical Mode Decomposition ◽  
Moving Average ◽  
Moving Load ◽  
Element Model ◽  
Detection Algorithm ◽  
Measured Signal ◽  
Intrinsic Mode Functions ◽  
Acceleration Response ◽  
Mode Decomposition

Empirical Mode Decomposition (EMD) is a technique that converts the measured signal into a number of basic functions known as intrinsic mode functions. The EMD-based damage detection algorithm relies on the principle that a sudden loss of stiffness in a structural member will cause a discontinuity in the measured response that can be detected through a distinctive spike in the filtered intrinsic mode function. Recent studies have shown that applying EMD to the acceleration response, due to the crossing of a constant load over a beam finite element model, can be used to detect a single damaged location. In this paper, the technique is further tested using the response of a discretized finite element beam with multiple damaged sections modeled as localized losses of stiffness. The ability of the algorithm to detect more than one damaged section is analysed for a variety of scenarios including a range of bridge lengths, speeds of the moving load and noise levels. The use of a moving average filter on the acceleration response, prior to applying EMD, is shown to improve the sensitivity to damage. The influence of the number of measurement points and their distance to the damaged sections on the accuracy of the predicted damage is also discussed.

scholarly journals SAR Target Detection Method Based on Empirical Mode Decomposition

2012 ◽  
Vol 6-7 ◽  
pp. 496-500
Author(s):  
Shi Qi Huang ◽  
Bei He Wang ◽  
Yi Hong Li ◽  
Bei Ge
Keyword(s):  
Signal Processing ◽  
Empirical Mode Decomposition ◽  
Target Detection ◽  
Detection Method ◽  
Detection Algorithm ◽  
Radar Signal ◽  
Sar Images ◽  
Processing Theory ◽  
Mode Decomposition ◽  
Non Stationary Signal

Empirical mode decomposition (EMD) is a new signal processing theory, and it is very much fitting for non-stationary signal processing, such as radar signal. So this paper proposes the new synthetic aperture radar (SAR) image target detection algorithm after analyzing the characteristics of EMD and SAR images. The proposed method performs the EMD operation, feature extraction, election and fusion, which can reduce the affection of speckle. Experimental results show that the proposed method is very effective.

A NOVEL APPROACH OF EDGE DETECTION VIA A FAST AND ADAPTIVE BIDIMENSIONAL EMPIRICAL MODE DECOMPOSITION METHOD

2010 ◽  
Vol 02 (02) ◽  
pp. 171-192 ◽  
Author(s):  
SHARIF M. A. BHUIYAN ◽  
JESMIN F. KHAN ◽  
REZA R. ADHAMI
Keyword(s):  
Edge Detection ◽  
Empirical Mode Decomposition ◽  
Detection Algorithm ◽  
Morphological Processing ◽  
Morphological Operations ◽  
Intrinsic Mode Functions ◽  
Novel Approach ◽  
Mode Decomposition ◽  
Edge Detectors ◽  
Bidimensional Empirical Mode Decomposition

A novel approach of edge detection is proposed that utilizes a bidimensional empirical mode decomposition (BEMD) method as the primary tool. For this purpose, a recently developed fast and adaptive BEMD (FABEMD) is used to decompose the given image into several bidimensional intrinsic mode functions (BIMFs). In FABEMD, order statistics filters (OSFs) are employed to get the upper and lower envelopes in the decomposition process, instead of surface interpolation, which enables fast decomposition and well-characterized BIMFs. Binarization and morphological operations are applied to the first BIMF obtained from FABEMD to achieve the desired edges. The proposed approach is compared with several other edge detection methodologies, which include a combination of classical BEMD and morphological processing, the Canny and Sobel edge detectors, as well as combinations of BEMD/FABEMD and Canny/Sobel edge detectors. Simulation results with real images demonstrate the efficacy and potential of the proposed edge detection algorithm employing FABEMD.

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