KEYWORDS: Terahertz radiation, Signal to noise ratio, Wavelets, Spectroscopy, Statistical modeling, System identification, Absorption, Signal processing, Signal attenuation, Classification systems
This work compares classification results of lactose, mandelic acid and dl-mandelic acid, obtained on the basis of their
respective THz transients. The performance of three different pre-processing algorithms applied to the time-domain
signatures obtained using a THz-transient spectrometer are contrasted by evaluating the classifier performance. A range
of amplitudes of zero-mean white Gaussian noise are used to artificially degrade the signal-to-noise ratio of the time-domain
signatures to generate the data sets that are presented to the classifier for both learning and validation purposes.
This gradual degradation of interferograms by increasing the noise level is equivalent to performing measurements
assuming a reduced integration time. Three signal processing algorithms were adopted for the evaluation of the complex
insertion loss function of the samples under study; a) standard evaluation by ratioing the sample with the background
spectra, b) a subspace identification algorithm and c) a novel wavelet-packet identification procedure. Within class and
between class dispersion metrics are adopted for the three data sets. A discrimination metric evaluates how well the three
classes can be distinguished within the frequency range 0.1 - 1.0 THz using the above algorithms.
We analyze the precision of a quasi-optical null-balance bridge reflectometer in measuring waveguide characteristic impedance and attenuation using a one-port de-embedding after taking into account errors due to imperfect coupling of two fundamental Gaussian beam. In order to determine the desired precision, we present in-waveguide measurements of characteristic impedance and attenuation for a WR-8 adjustable precision short in the 75-110 GHz frequency range using a Hewlett-Packard HP 8510 vector network analyzer.
The potential of optical fibres in monitoring water uptake from plants is considered. Applications include an optical potometer that monitors water uptake from individual roots, the detection of xylem cavitation using audio acoustic emissions with an interferometric force feedback microphone, an optical displacement transducer that detects changes in leaf thickness in relation to leaf water potential, and the use of fluorescence to monitor water uptake and translocation.
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