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Frequency domain
signal can be analyzed using a discrete frequency domain. Dually, a discrete-time signal gives rise to a periodic frequency spectrum. Combining these two
Discrete frequency domain
A discrete frequency domain is a frequency domain that is discrete rather than continuous. For example, the discrete Fourier transform maps a function
Bilinear transform
can be used to warp the frequency response of any discrete-time linear system (for example to approximate the non-linear frequency resolution of the human
Nyquist frequency
The Nyquist frequency, named after electronic engineer Harry Nyquist, is half of the sampling rate of a discrete signal processing system. It is sometimes
Discrete Fourier transform
equally-spaced samples of the discrete-time Fourier transform (DTFT), which is a complex-valued function of frequency. The interval at which the DTFT
Time domain
in the case of discrete time. An oscilloscope is a tool commonly used to visualize real-world signals in the time domain. A time-domain graph shows how
Discrete wavelet transform
appropriately constructed top-hat filters in frequency space). Wavelet packet transforms are also related to the discrete wavelet transform. Complex wavelet transform
Discrete-time Fourier transform
original discrete samples. The DTFT itself is a continuous function of frequency, but discrete samples of it can be readily calculated via the discrete Fourier
Discrete spectrum
the continuous part representing the ionization. Band structure Discrete frequency domain Decomposition of spectrum (functional analysis) Essential spectrum
Voice frequency
sampling frequency (8 kHz) must be at least twice the highest component of the voice frequency via appropriate filtering prior to sampling at discrete times