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Spectral leakage is the creation of new frequency components by linear operations on a function of time or frequency Only frequencies that coincide with the basis function will project on a single basis vector, such as shown in fig Learn about the causes, effects and types of spectral leakage, and how to choose a window function for spectral analysis.
The spectral plots in fig Window functions and spectral leakage the purpose of window functions is to minimize a phenomenon called spectral leakage, which is the result of selecting a finite time interval and a nonorthogonal trigonometric basis function over the interval of analysis 6.12 illustrate another price that we must pay to counteract leakage
If we do have analysis frequencies in the signal, applying windowing will spread some of their energy across the spectrum.
Spectral leakage due to fft is caused by Mismatch between desired tone and chosen frequency resolution, time limiting an observation Explore the world of spectral leakage and its effects on spectral analysis Learn how to identify and mitigate spectral leakage.
The spectrum you get by using a fft, therefore, is not the actual spectrum of the original signal, but a smeared version It appears as if the energy at one frequency has leaked out into all the other frequencies This phenomenon is known as spectral leakage. Learn how spectral leakage occurs when the input signal is not a whole number of periods and the energy leaks out to the surrounding frequency bins
See examples of sine wave frequency responses with and without leakage and how it affects the amplitude and resolution.
Returning to case of the spectrum analyzer, the fourier transform, leakage causes a conflict of interests It is expected to display the fft of the current input, taking only the last part of it However, this is a very sharpened window that causes broad leakage A wider window causes less distortion, but uses older signal data.
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