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Length L FIR Frame Filters

To avoid time aliasing, we restrict the filter length to a maximum of $ L$ samples. Since $ H_m(\omega_k)$ is an arbitrary multiplicative weighting of the $ m$ th spectral frame, the frame filter need not be causal. For odd $ L$ , the filter impulse response indices may run from $ -L_h$ to $ L_h$ , where

$\displaystyle L_h \isdef \frac{L-1}{2}$ (9.43)

This gives

\begin{eqnarray*}
y(n) &=& \sum_{r=-L_h}^{L_h} x(n-r) {\hat h}_{n-r}(r) \\
&=& x(n) {\hat h}_n(0) \\
& & + x(n-1) {\hat h}_{n-1}(1) + \cdots + x(n-L_h) {\hat h}_{n-L_h}(L_h) \\
& & + x(n+1) {\hat h}_{n+1}(-1) + \cdots + x(n+L_h) {\hat h}_{n+L_h}(-L_h)
\end{eqnarray*}

This is the general length $ L$ time-varying FIR filter convolution sum for time $ n$ , when $ L$ is odd.


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``Spectral Audio Signal Processing'', by Julius O. Smith III, W3K Publishing, 2011, ISBN 978-0-9745607-3-1.
Copyright © 2016-07-18 by Julius O. Smith III
Center for Computer Research in Music and Acoustics (CCRMA),   Stanford University
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