A Novel Data-Driven Cardiac Gating Signal Extraction Method for PET

2019 ◽  
Vol 38 (2) ◽  
pp. 629-637 ◽  
Author(s):  
Tao Feng ◽  
Jizhe Wang ◽  
Yun Dong ◽  
Jun Zhao ◽  
Hongdi Li
Author(s):  
Dimas Bagus Wiranatakusuma ◽  
Ricky Dwi Apriyono

There seems to be no single country that can escape from currency crises. This paper aims to answer: (i) How to determine exchange market pressure (EMP)? and (ii) To what extent the contribution of selected indicators to the prediction of currency crises?. The study adopts indicators developed by Kaminski, et.al (1999) by using signal extraction method as the early warning system (EWS) mechanism. By employing four selected variables, International reserve, real exchange rates, credit growth, and domestic inflation, the findings suggest the periods of crises fluctuated over the observations under various thresholds. The EMP touched the Kaminsky's line only during the Asian and global financial crises. Meanwhile, the Garcia's, Park's and Lestano's line was passed through frequently over the observations, and it implies that the financial system was cyclically under shocks. In conclusion, the currency crises frequently appear attacking Indonesia's financial system so that need to be mitigated by net open position (NOP) as macroprudential instrument.


2019 ◽  
Vol 133 ◽  
pp. S1139-S1140
Author(s):  
A. Akintonde ◽  
H. Grimes ◽  
S. Moinuddin ◽  
R.A. Sharma ◽  
J. McClelland ◽  
...  

2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Chao Huang ◽  
Xin Xu ◽  
Dunge Liu ◽  
Wanhua Zhu ◽  
Xiaojuan Zhang ◽  
...  

It is a technical challenge to effectively remove the influence of magnetic noise from the vicinity of the receiving sensors on low-frequency magnetic communication. The traditional denoising methods are difficult to extract high-quality original signals under the condition of low SNR (the signal-to-noise ratio). In this paper, we analyze the numerical characteristics of the low-frequency magnetic field and propose the algorithms of the fast optimization of blind source separation (FOBSS) and the frequency-domain correlation extraction (FDCE). FOBSS is based on blind source separation (BSS). Signal extraction of low SNR can be implemented through FOBSS and FDCE. This signal extraction method is verified in multiple field experiments which can remove the magnetic noise by about 25 dB or more.


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