EMI-debugging of complex systems using different time, modulation, STFFT and frequency domain signal analysis techniques

Author(s):  
Zhe Li ◽  
D. Pommerenke
Sensors ◽  
2013 ◽  
Vol 13 (5) ◽  
pp. 6605-6635 ◽  
Author(s):  
Mahmoud Al-Kadi ◽  
Mamun Reaz ◽  
Mohd Ali

1980 ◽  
Author(s):  
Donald E. Gustafson ◽  
John S. Eterno ◽  
Wolfram Jarisch

2004 ◽  
Vol 5 (3) ◽  
pp. 211-221 ◽  
Author(s):  
Autumn Schumacher

Analysis techniques derived from linear and non-linear dynamics systems theory qualify and quantify physiological signal variability. Both clinicians and researchers use physiological signals in their scopes of practice. The clinician monitors patients with signal-analysis technology, and the researcher analyzes physiological data with signal-analysis techniques. Understanding the theoretical basis for analyzing physiological signals within one’s scope of practice ensures proper interpretation of the relationship between physiological function and signal variability. This article explains the concepts of linear and nonlinear signal analysis and illustrates these concepts with descriptions of power spectrum analysis and recurrence quantification analysis. This article also briefly describes the relevance of these 2 techniques to R-to-R wave interval (i.e., heart rate variability) signal analysis and demonstrates their application to R-to-R wave interval data obtained from an isolated rat heart model.


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