scholarly journals Time Series Analysis of Postharvest Ripening of Plum Fruit by Near Infrared Spectroscopy.

1996 ◽  
Vol 43 (4) ◽  
pp. 382-387 ◽  
Author(s):  
Takumi ONDA ◽  
Yoshihiro KOMIYAMA ◽  
Chikao OTOGURO
Keyword(s):  
Time Series ◽  
Infrared Spectroscopy ◽  
Time Series Analysis ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Series Analysis ◽  
Postharvest Ripening

scholarly journals HomER: a review of time-series analysis methods for near-infrared spectroscopy of the brain

2009 ◽  
Vol 48 (10) ◽  
pp. D280 ◽  
Author(s):  
Theodore J. Huppert ◽  
Solomon G. Diamond ◽  
Maria A. Franceschini ◽  
David A. Boas
Keyword(s):  
Time Series ◽  
Infrared Spectroscopy ◽  
Time Series Analysis ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Series Analysis ◽  
Analysis Methods ◽  
The Brain

Time series analysis in near-infrared spectroscopy (NIRS) aided by fuzzy C-means (FCM) and wavelet transforms

NeuroImage ◽  
2001 ◽  
Vol 13 (6) ◽  
pp. 175
Author(s):  
Syoji Kobashi ◽  
Yuri T. Kitamura ◽  
Mika Otsuki ◽  
Yutaka Hata ◽  
Hiroaki Naritomi ◽  
...  
Keyword(s):  
Time Series ◽  
Infrared Spectroscopy ◽  
Time Series Analysis ◽  
Near Infrared Spectroscopy ◽  
Wavelet Transforms ◽  
Near Infrared ◽  
Fuzzy C Means ◽  
Series Analysis

scholarly journals Multifractals Properties on the Near Infrared Spectroscopy of Human Brain Hemodynamic

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Truong Quang Dang Khoa ◽  
Vo Van Toi
Keyword(s):  
Time Series ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Real Life ◽  
Multifractal Spectrum ◽  
Singular Behavior ◽  
Maximum Expansion ◽  
Experimental Time Series ◽  
Hölder Exponents

Nonlinear physics presents us with a perplexing variety of complicated fractal objects and strange sets. Naturally one wishes to characterize the objects and describe the events occurring on them. Moreover, most time series found in “real-life” applications appear quite noisy. Therefore, at almost every point in time, they cannot be approximated either by the Taylor series or by the Fourier series of just a few terms. Many experimental time series have fractal features and display singular behavior, the so-called singularities. The multifractal spectrum quantifies the degree of fractals in the processes generating the time series. A novel definition is proposed called full-width Hölder exponents that indicate maximum expansion of multifractal spectrum. The obtained results have demonstrated the multifractal structure of near-infrared spectroscopy time series and the evidence for brain imagery activities.

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