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Simple Examples of Perfect Reconstruction

If we can arrange to have

$\displaystyle \zbox {\bold{R}(z)\bold{E}(z) = \bold{I}_N}
$

then the filter bank will reduce to the simple system shown in Fig.11.24.

Figure: Simplified filter bank when $ R(z)$ inverts $ E(z)$.
\begin{figure}\input fig/polyNchanI.pstex_t
\end{figure}

Thus, when $ R=N$ and $ \bold{R}(z)\bold{E}(z)=\bold{I}_N$, we have a simple parallelizer/serializer, which is perfect-reconstruction by inspection: Referring to Fig.11.24, think of the input samples $ x(n)$ as ``filling'' a length $ N-1$ delay line over $ N-1$ sample clocks. At time 0, the downsamplers and upsamplers ``fire'', transferring $ x(0)$ (and $ N-1$ zeros) from the delay line to the output delay chain, summing with zeros. Over the next $ N-1$ clocks, $ x(0)$ makes its way toward the output, and zeros fill in behind it in the output delay chain. Simultaneously, the input buffer is being filled with samples of $ x(n)$. At time $ N-1$, $ x(0)$ makes it to the output. At time $ N$, the downsamplers ``fire'' again, transferring a length $ N$ ``buffer'' [ $ x(1\texttt{:}N)$] to the upsamplers. On the same clock pulse, the upsamplers also ``fire'', transferring $ N$ samples to the output delay chain. The bottom-most sample [ $ x(n-N+1)=x(1)$] goes out immediately at time $ N$. Over the next $ N-1$ sample clocks, the length $ N-1$ output buffer will be ``drained'' and refilled by zeros. Simultaneously, the input buffer will be replaced by new samples of $ x(n)$. At time $ 2N$, the downsamplers and upsamplers ``fire'', and the process goes on, repeating with period $ N$. The output of the $ N$-way parellelizer/serializer is therefore

$\displaystyle {\hat x}(n) = x(n-N+1)
$

and we have perfect reconstruction.


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Next: Sliding Polyphase Filter Bank

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.


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