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One of the main reasons for using a frequency-domain representation of a problem is to simplify the mathematical analysis. For mathematical systems governed by linear differential equations, a very important class of systems with many real-world applications, converting the description of the system from the time domain to a frequency domain converts the differential equations to algebraic ...
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 ...
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.
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 ...
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 ...
Since it is a time-domain method, solutions can cover a wide frequency range with a single simulation run, provided the time step is small enough to satisfy the Nyquist–Shannon sampling theorem for the desired highest frequency. FDTD belongs in the general class of grid-based differential time-domain numerical modeling methods.
The spectrum of a chirp pulse describes its characteristics in terms of its frequency components. This frequency-domain representation is an alternative to the more familiar time-domain waveform, and the two versions are mathematically related by the Fourier transform.