Nyquist(N) Windows

In (9.5) of the previous section, we derived that the FBS reconstruction sum gives

where . From this we see that if (where is the window length and is the DFT size), as is normally the case, then for . This is the Fourier dual of the ``strong COLA constraint'' for OLA (see §8.3.2). When it holds, we have

This is simply a gain term, and so we are able to recover the original signal exactly. (Zero-phase windows are appropriate here.)

If the window length is larger than the number of analysis frequencies (), we can still obtain perfect reconstruction provided

When this holds, we say the window is . (This is the dual of the weak COLA constraint introduced in §8.3.1.) Portnoff windows, discussed in §9.7, make use of this result; they are longer than the DFT size and therefore must be used in time-aliased form [55]. An advantage of Portnoff windows is that they give reduced overlap among the channel filter passbands. In the limit, a Portnoff window can approach a sinc function having its zero-crossings at all nonzero multiples of samples, thereby yielding an ideal channel filter with bandwidth . Figure 9.16 compares example Hamming and Portnoff windows.

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Order a Hardcopy of Spectral Audio Signal Processing

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written by Julius Orion Smith III
Julius Smith's background is in electrical engineering (BS Rice 1975, PhD Stanford 1983). He is presently Professor of Music and Associate Professor (by courtesy) of Electrical Engineering at Stanford's Center for Computer Research in Music and Acoustics (CCRMA), teaching courses and pursuing research related to signal processing applied to music and audio systems. See http://ccrma.stanford.edu/~jos/ for details.