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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).
In signal processing, time–frequency analysis comprises those techniques that study a signal in both the time and frequency domains simultaneously, using various time–frequency representations. Rather than viewing a 1-dimensional signal (a function, real or complex-valued, whose domain is the real line) and some transform (another function ...
Recall that decimation of sampled data in one domain (time or frequency) produces overlap (sometimes known as aliasing) in the other, and vice versa. Compared to an L {\displaystyle L} -length DFT, the s N {\displaystyle s_{_{N}}} summation/overlap causes decimation in frequency, [ 1 ] : p.558 leaving only DTFT samples least affected by ...
A time–frequency representation (TFR) is a view of a signal (taken to be a function of time) represented over both time and frequency. [1] Time–frequency analysis means analysis into the time–frequency domain provided by a TFR. This is achieved by using a formulation often called "Time–Frequency Distribution", abbreviated as TFD.
The trade-off between the compaction of a function and its Fourier transform can be formalized in the form of an uncertainty principle by viewing a function and its Fourier transform as conjugate variables with respect to the symplectic form on the time–frequency domain: from the point of view of the linear canonical transformation, the ...
Noting that a signal can be recovered from a particular distribution under certain conditions, given a certain TFD ρ 1 (t,f) representing the signal in a joint time–frequency domain, another, different, TFD ρ 2 (t,f) of the same signal can be obtained to calculate any other distribution, by simple smoothing or filtering; some of these ...
For cases where frequency information appears briefly in the signal or generally varies over time, alternatives like the short-time Fourier transform, discrete wavelet transforms, or discrete Hilbert transform can be more suitable. [49] [50] These transforms allow for localized frequency analysis by capturing both frequency and time-based ...
More generally, convolution in one domain (e.g., time domain) equals point-wise multiplication in the other domain (e.g., frequency domain). Other versions of the convolution theorem are applicable to various Fourier-related transforms.