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In order to view a signal (taken to be a function of time) represented over both time and frequency axis,
time–frequency representation A time–frequency representation (TFR) is a view of a signal (taken to be a function of time) represented over both time and frequency. Time–frequency analysis means analysis into the time–frequency domain provided by a TFR. This is achieved b ...
is used.
Spectrogram A spectrogram is a visual representation of the spectrum of frequencies of a signal as it varies with time. When applied to an audio signal, spectrograms are sometimes called sonographs, voiceprints, or voicegrams. When the data are represen ...
is one of the most popular time-frequency representation, and generalized spectrogram, also called "two-window spectrogram", is the generalized application of spectrogram.


Definition

The definition of the spectrogram relies on the Gabor transform (also called short-time Fourier transform, for short STFT), whose idea is to localize a signal in time by multiplying it with translations of a window function w(t). The definition of spectrogram is :S(t,f) = (t,f)G_^*(t,f)=, (t,f), ^2, where denotes the
Gabor Transform The Gabor transform, named after Dennis Gabor, is a special case of the short-time Fourier transform. It is used to determine the sinusoidal frequency and phase content of local sections of a signal as it changes over time. The function to be transf ...
of x(t). Based on the spectrogram, the generalized spectrogram is defined as: :S(t,f) = (t,f)G_^*(t,f), where: :\left( \right) = \int_^\infty :\left( \right) = \int_^\infty For w_1(t) = w_2(t)=w(t), it reduces to the classical spectrogram: :S(t,f) = (t,f)G_^*(t,f)=, (t,f), ^2 The feature of Generalized spectrogram is that the window sizes of w_1(t) and w_2(t) are different. Since the time-frequency resolution will be affected by the window size, if one choose a wide w_1(t) and a narrow w_1(t) (or the opposite), the resolutions of them will be high in different part of spectrogram. After the multiplication of these two Gabor transform, the resolutions of both time and frequency axis will be enhanced.


Properties

;Relation with Wigner Distribution :\mathcal_(t,f)(x,w) = Wig (w_1', w_2')*Wig (t,f)(x, w), :where w_1'(s):=w_1(-s), w_2'(s):=w_2(-s) ;Time marginal condition :The generalized spectrogram \mathcal_(t,f)(x,w) satisfies the time marginal condition if and only if w_1w_2' = \delta, :where \delta denotes the
Dirac delta function In mathematics, the Dirac delta distribution ( distribution), also known as the unit impulse, is a generalized function or distribution over the real numbers, whose value is zero everywhere except at zero, and whose integral over the entire ...
;Frequency marginal condition :The generalized spectrogram \mathcal_(t,f)(x,w) satisfies the frequency marginal condition if and only if w_1w_2' = \delta, :where \delta denotes the
Dirac delta function In mathematics, the Dirac delta distribution ( distribution), also known as the unit impulse, is a generalized function or distribution over the real numbers, whose value is zero everywhere except at zero, and whose integral over the entire ...
;Conservation of energy :The generalized spectrogram \mathcal_(t,f)(x,w) satisfies the conservation of energy if and only if (w_1,w_2) = 1. ;Reality analysis :The generalized spectrogram \mathcal_(t,f)(x,w) is real if and only if w_1=C w_2 for some C\in \R.


References


Class notes of Time frequency analysis and wavelet transform -- from Prof. Jian-Jiun Ding's course website
* P. Boggiatto, G. De Donno, and A. Oliaro, â
Two window spectrogram and their integrals
" Advances and Applications, vol. 205, pp. 251–268, 2009. {{refend Time–frequency analysis