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It is worth noting that the information in the power density spectrum of a signal is identical to the ACF of the signal.
Combining a linear dynamical filter system and a nonlinear transform makes it possible to adapt the power density spectrum of an artificial stationary process as well as its probability distribution function to given quantities.
This can be easily explained in this observation by the photocurrent density spectrum of the rear surface recombination as shown in Fig. 4b.
The collection of diffuse scattering plays an important role in the features of an optical density spectrum of a macro-particulate system.
The parameters n̄ and Φ were computed as: (2) n ¯ ∝ 〈 ω (0 ) 〉 / i 0 2, (3) Φ ∝ 〈 ω (1 ) 〉 / i 0 2, where i 0 2 is the mean photo-electric current, and 〈 ω(0)〉 and 〈 ω(1)〉 are the 0th and 1st moments of the power density spectrum of i(t).
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Fig. 4 a EQE spectra and b photocurrent density spectra of the rear surface recombination under various surface recombination velocities.
Figure 2a,b shows the noise density spectrums of the FM- and HAM-KPFMs detected signals obtained at a modulation frequency of 500 Hz for FM-KPFM and 1.05 MHz for HAM-KPFM.
Figures 6a-c and 7a-c represent the peak ion density spectra of fifteen masses between 24 and 100 amu due to ablation of micrometeoroids and meteoroids respectively at velocities 10 km/s, 18 km/s and 30 km/s.
In Fig. 2a, a typical power density spectra of the ion current fluctuations is shown.
The penetration of antibiotics into the channel can also be measured by analysing the power density spectra of the ion current.
We then estimated the absorption rate spectra of each pigment at the cornea (Scornea) by the formula, Sconea = 10−[Lens+Macular]×Sretina, where Lens and Macular represent the optical density spectra of lens and macular pigment, respectively, measured in humans [65].
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