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APPLICATION NOTE AN014 Understanding FFTWindows

UnderstandingFFTW indowsAPPLICATION NOTEAN014 IntroductionFFT based measurements are subject to errors froman effect known as leakage. This effect occurs whenthe FFT is computed from of a block of data which isnot periodic. To correct this problem appropriate win-dowing functions must be applied. The user mustchoose the appropriate window function for the specif-ic APPLICATION . When windowing is not applied correct-ly, then errors may be introduced in the FFT ampli-tude, frequency or overall shape of the spectrum . Thisapplication note describes the phenomenon of leak-age, the various windowing functions and theirstrengths and weaknesses, and examples are givenfor various Background Most dynamic signal analyzers (Figure 1) computetime and frequency measurements.

calculation of the spectrum. This means that more aver-ages must be taken to get a good statistical representa-tion of the spectrum, increasing the time to complete the measurement. Overlap processing is a feature that is available in most signal analyzers that can recover the lost data and reduce the measurement time. This pro-

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