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Periodicity is one of the basic assumptions made in FFT-based frequency analysis. The FFT algorithm implicitly assumes that every block of acquired data indefinitely repeats in both positive and negative time. Windowing is one method of ensuring periodicity.

Windowing multiplies the time-domain data by a window function before the FFT is performed. Window functions typically have a value of zero at the start and end of the measurement period. The following front panel shows how a signal that is not the same at the start and end of the measurement period appears not to be periodic and how the signal becomes periodic when multiplied by a window function.

The windows that the NI Sound and Vibration Measurement Suite supports and their equivalent noise bandwidths (ENBW) are listed in the following table.

Window	ENBW
None	1
Hanning	1.50
Hamming	1.36
Blackman-Harris	1.71
Exact Blackman	1.69
Blackman	1.73
Flat Top	3.77
4 Term Blackman-Harris	2.00
7 Term Blackman-Harris	2.63
Low Sidelobe	2.22
Blackman Nuttall	1.98
Triangle	1.33
Barlett-Hanning	1.46
Bohman	1.79
Parzen	1.92
Welch	1.20
Kaiser	3.85
Dolph-Chebyshev	1.40
Gaussian	1
Force-Exponential	N/A

Note  ENBW is a property of the window applied to the signal. You can find a complete list of supported time-domain windows in the window control of the SVFA Power Spectrum VI.

Strategies for Choosing Windows

Typically, you use a window with a low ENBW to resolve peak frequencies. You use a window with a high ENBW to resolve peak amplitudes. Use the Force-Exponential window for shock and impulse testing where the stimulus signal exhibits transient behavior after the impact event, or where the response of the signal does not decay to zero in the measurement period.

Note  The Force-Exponential window is supported only for dual-channel measurements made with the Baseband FFT VIs and the Baseband Subset VIs.