A hybrid analysis method for multi‐class queueing networks with multi‐server nodes

2013 ◽  
Vol 54 (4) ◽  
pp. 1541-1547 ◽  
Author(s):  
Boualem Rabta ◽  
Reinhold Schodl ◽  
Gerald Reiner ◽  
Johannes Fichtinger
2010 ◽  
Vol 37 (8) ◽  
pp. 1472-1487 ◽  
Author(s):  
R. Andriansyah ◽  
T. Van Woensel ◽  
F.R.B. Cruz ◽  
L. Duczmal

2014 ◽  
Vol 78 ◽  
pp. 131-138 ◽  
Author(s):  
Qiuhong Jiang ◽  
Tao Li ◽  
Zhichao Liu ◽  
Hongchao Zhang ◽  
Keda Ren

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Xiangkui Wan ◽  
Kanghui Yan ◽  
Linlin Zhang ◽  
Yanjun Zeng

T-wave alternans (TWA) in surface electrocardiograph (ECG) signals has been recognized as a marker of cardiac electrical instability and is hypothesized to be associated with increased risk for ventricular arrhythmias among patients. A novel time-domain TWA hybrid analysis method (HAM) utilizing the correlation method and least squares regression technique is described in this paper. Simulated ECGs containing artificial TWA (cases of absence of TWA and presence of stationary or time-varying or phase-reversal TWA) under different baseline wanderings are used to test the method, and the results show that HAM has a better ability of quantifying TWA amplitude compared with the correlation method (CM) and adapting match filter method (AMFM). The HAM is subsequently used to analyze the clinical ECGs, and results produced by the HAM have, in general, demonstrated consistency with those produced by the CM and the AMFM, while the quantifying TWA amplitudes by the HAM are universally higher than those by the other two methods.


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