# Introduction to Digital FiltersAllpass Filters

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# Allpass Filters

This appendix addresses the general problem of characterizing all digital allpass filters, including multi-input, multi-output (MIMO) allpass filters. As a result of including the MIMO case, the mathematical level is a little higher than usual for this book. The reader in need of more background is referred to [84,37,98].Our first task is to show that losslessness implies allpass.

Definition: A linear, time-invariant filter is said to be lossless if it preserves signal energy for every input signal. That is, if the input signal is , and the output signal is , then we have

In terms of the signal norm , this can be expressed more succinctly as

Notice that only stable filters can be lossless, since otherwise can be infinite while is finite. We further assume all filters are causalC.1 for simplicity. It is straightforward to show the following:

Theorem: A stable, linear, time-invariant (LTI) filter transfer function is lossless if and only if

That is, the frequency response must have magnitude 1 everywhere over the unit circle in the complex plane.

Proof: We allow the signals and filter impulse response to be complex. By Parseval's theorem [84] for the DTFT, we have,C.2 for any signal ,

i.e.,

Thus, Parseval's theorem enables us to restate the definition of losslessness in the frequency domain:

where because the filter is LTI. Thus, is lossless by definition if and only if

 (C.1)

Since this must hold for all , we must have for all , except possibly for a set of measure zero (e.g., isolated points which do not contribute to the integral) [73]. If is finite order and stable, is continuous over the unit circle, and its modulus is therefore equal to 1 for all .

We have shown that every lossless filter is allpass. Conversely, every unity-gain allpass filter is lossless.

Subsections
Previous: Elementary Filter Problems
Next: Allpass Examples

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About the Author: 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 (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.