Window functions reduce spectral leakage in FFT analysis.
Truncating a signal to finite length causes spectral leakage. Windows (Hann, Hamming, Blackman, Kaiser) taper the ends, lowering side-lobes at the cost of wider main lobe. Rectangular is best for transients and exactly periodic data. Window choice trades resolution vs dynamic range.
Hann window is the default for general spectrum analysis.
Windows reduce the spectral leakage that appears when a finite block is analysed, which makes peaks clearer and amplitudes more accurate.
Window functions reduce spectral leakage in FFT analysis.
Windows reduce the spectral leakage that appears when a finite block is analysed, which makes peaks clearer and amplitudes more accurate.
Energy from one frequency spreads into neighbouring bins because the block does not contain a whole number of periods.
Windows widen the main peak and reduce sidelobes, so they improve dynamic range at the cost of frequency resolution.
Typical applications include choosing a Hann window before computing the spectrum of a vibration record, reducing leakage when a tone does not fit exactly into the block and comparing amplitude accuracy and sidelobe level for two window functions.
Study "Fast Fourier transform" first (topic 28 of 101 in Signals, Control & Comms). It covers the groundwork this topic builds on.
Coherent gain. ENBW. Overlap-add processing.
Hann window is the default for general spectrum analysis.
The next topic is "Z-transform", which builds directly on this one.
It is classed as Beginner in Signals, Control & Comms (topic 29 of 101). It is an entry-level topic. It relies only on basic school mathematics and the ideas introduced earlier in this discipline.
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