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when windowing in DSP in time domain one multiplies all recorded time samples with a weighting factor (hanning, hamming, etc.), followed by a fourier transform (FFT) to reduce sidelobes in the spectral domain.

But now when thinking about starting up in frequency domain where I have multiplied my frequency data with a rectangular window, i.e. I have only non-zero frequencies from fstart to fend ( ... 0 0 0 0 0 0 0 fstart f1 f2 f3 f4 f5 fend 0 0 0 0 ... ). (or alternatively I only have frequency datas recorded at finite points.)What happens to my time domain data after performing the inverse FFT due to the rectangular window?

But in general: How do one has to perform windowing in frequency domain? Really by multiplying the "origianal" (i.e. time domain) window-coefficients with the spectral components? Or performing convolution (with the origignal window, or the fourier transformed coefficients?) since this is the fourier-pair to multiplication?

Thanks for any ideas.

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# Windowing (DSP)

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