Watermarking of ECG signals compressed using Fourier decomposition method

Author(s):  
Prashant Mani Tripathi ◽  
Ashish Kumar ◽  
Rama Komaragiri ◽  
Manjeet Kumar
2021 ◽  
pp. 146808742098819
Author(s):  
Wang Yang ◽  
Cheng Yong

As a non-intrusive method for engine working condition detection, the engine surface vibration contains rich information about the combustion process and has great potential for the closed-loop control of engines. However, the measured engine surface vibration signals are usually induced by combustion as well as non-combustion excitations and are difficult to be utilized directly. To evaluate some combustion parameters from engine surface vibration, the tests were carried out on a single-cylinder diesel engine and a new method called Fourier Decomposition Method (FDM) was used to extract combustion induced vibration. Simulated and test results verified the ability of the FDM for engine vibration analysis. Based on the extracted vibration signals, the methods for identifying start of combustion, location of maximum pressure rise rate, and location of peak pressure were proposed. The cycle-by-cycle analysis of the results show that the parameters identified based on vibration and in-cylinder pressure have the similar trends, and it suggests that the proposed FDM-based methods can be used for extracting combustion induced vibrations and identifying the combustion parameters.


Measurement ◽  
2021 ◽  
pp. 109837
Author(s):  
Jinde Zheng ◽  
Siqi Huang ◽  
Haiyang Pan ◽  
Jinyu Tong ◽  
Chengjun Wang ◽  
...  

Author(s):  
R. Srivastava ◽  
Milind A. Bakhle ◽  
Theo G. Keith ◽  
G. L. Stefko

In the present work a comparative study of phase-lagged boundary condition methods is carried out. The relative merits and advantages of time-shifted and the Fourier decomposition methods are compared. Both methods are implemented in a time marching Euler/Navier-Stokes solver and are applied to a flat plate helical fan with harmonically oscillating blades to perform the study. Results were obtained for subsonic as well as supersonic inflows. Results for subsonic inflow showed good comparisons with published results and between the two methods along with comparable computational costs. For the supersonic inflow, despite the presence of shocks at the periodic boundary results from both the methods compared well, however, Fourier decomposition method was computationally more expensive. For linear flowfield Fourier decomposition method is best suited, especially for work-station environment. The time-shifted method is better suited for CRAY category of computers where fast input-output devices are available.


ECG is a graphical representation of heart’s electrical activity such as electrical reploarization and depolarization of heart. It is an important non- stationary signal which contains the necessary information about the heart functioning so that it can be used to identify different abnormalities in heart beats and also to identify different diseases of human beings. Classification is an important process in ECG signal analysis and cardiac diseases diagnosis process. Different ECG signals as well as ECG parameters such as heart beats, features can be classified according to requirement. In this paper different classification networks have studied. SVM classifier with empirical mode decomposition represented the maximum accuracy of 99.54%. Any optimization technique can be used to increase the accuracy of SVM classifier with suitable decomposition method such as variatinal mode decomposition.


2020 ◽  
Vol 32 (3) ◽  
pp. 035003
Author(s):  
Minqiang Deng ◽  
Aidong Deng ◽  
Jing Zhu ◽  
Yaowei Shi ◽  
Yang Liu ◽  
...  

2020 ◽  
Vol 61 ◽  
pp. 102005 ◽  
Author(s):  
Binish Fatimah ◽  
Pushpendra Singh ◽  
Amit Singhal ◽  
Ram Bilas Pachori

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