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  2. Voigt profile - Wikipedia

    en.wikipedia.org/wiki/Voigt_profile

    The pseudo-Voigt profile (or pseudo-Voigt function) is an approximation of the Voigt profile V(x) using a linear combination of a Gaussian curve G(x) and a Lorentzian curve L(x) instead of their convolution. The pseudo-Voigt function is often used for calculations of experimental spectral line shapes.

  3. Gaussian function - Wikipedia

    en.wikipedia.org/wiki/Gaussian_function

    The peak is "well-sampled", so that less than 10% of the area or volume under the peak (area if a 1D Gaussian, volume if a 2D Gaussian) lies outside the measurement region. The width of the peak is much larger than the distance between sample locations (i.e. the detector pixels must be at least 5 times smaller than the Gaussian FWHM).

  4. Spectral line shape - Wikipedia

    en.wikipedia.org/wiki/Spectral_line_shape

    Ideal line shapes include Lorentzian, Gaussian and Voigt functions, whose parameters are the line position, maximum height and half-width. [1] Actual line shapes are determined principally by Doppler, collision and proximity broadening. For each system the half-width of the shape function varies with temperature, pressure (or concentration) and

  5. Frequency domain - Wikipedia

    en.wikipedia.org/wiki/Frequency_domain

    The inverse Fourier transform converts the frequency-domain function back to the time-domain function. A spectrum analyzer is a tool commonly used to visualize electronic signals in the frequency domain. A frequency-domain representation may describe either a static function or a particular time period of a dynamic function (signal or system).

  6. MUSIC (algorithm) - Wikipedia

    en.wikipedia.org/wiki/MUSIC_(algorithm)

    MUSIC outperforms simple methods such as picking peaks of DFT spectra in the presence of noise, when the number of components is known in advance, because it exploits knowledge of this number to ignore the noise in its final report.

  7. Spectral density - Wikipedia

    en.wikipedia.org/wiki/Spectral_density

    The spectral density is a function of frequency, not a function of time. However, the spectral density of a small window of a longer signal may be calculated, and plotted versus time associated with the window. Such a graph is called a spectrogram.

  8. Logarithmic decrement - Wikipedia

    en.wikipedia.org/wiki/Logarithmic_decrement

    The logarithmic decrement can be obtained e.g. as ln(x 1 /x 3).Logarithmic decrement, , is used to find the damping ratio of an underdamped system in the time domain.. The method of logarithmic decrement becomes less and less precise as the damping ratio increases past about 0.5; it does not apply at all for a damping ratio greater than 1.0 because the system is overdamped.

  9. Two-dimensional correlation analysis - Wikipedia

    en.wikipedia.org/wiki/Two-dimensional...

    As the peaks at (x,y) in the 2D synchronous spectrum are a measure for the correlation between the intensity changes at x and y in the original data, these main diagonal peaks are also called autopeaks and the main diagonal signal is referred to as autocorrelation signal. The off-diagonal cross-peaks can be either positive or negative. On the ...