Sign in

username:

password:



Not a member?

Search Online Books



Search tips

Free Online Books

Chapters

Chapter Contents:

Search Introduction to Digital Filters

  

Book Index | Global Index


Would you like to be notified by email when Julius Orion Smith III publishes a new entry into his blog?

  

Time-Invariant Filters

In plain terms, a time-invariant filter (or shift-invariant filter) is one which performs the same operation at all times. It is awkward to express this mathematically by restrictions on Eq.$ \,$(4.2) because of the use of $ x(\cdot)$ as the symbol for the filter input. What we want to say is that if the input signal is delayed (shifted) by, say, $ N$ samples, then the output waveform is simply delayed by $ N$ samples and unchanged otherwise. Thus $ y(\cdot)$, the output waveform from a time-invariant filter, merely shifts forward or backward in time as the input waveform $ x(\cdot)$ is shifted forward or backward in time.



Definition. A digital filter $ {\cal L}_n$ is said to be time-invariant if, for every input signal $ x$, we have

$\displaystyle {\cal L}_n\{$SHIFT$\displaystyle _N\{x\}\}$ $\displaystyle =$ $\displaystyle {\cal L}_{n-N}\{x(\cdot)\}\;=\;y(n-N)$  
  $\displaystyle =$ SHIFT$\displaystyle _{N,n}\{y\},
\protect$ (5.5)

where the $ N$-sample shift operator is defined by

   SHIFT$\displaystyle _{N,n}\{x\}\isdef x(n-N).
$

On the signal level, we can write

   SHIFT$\displaystyle _N\{x\} \isdef x(\cdot-N).
$

Thus, SHIFT$ _N\{x\}$ denotes the waveform $ x(\cdot)$ shifted right (delayed) by $ N$ samples. The most common notation in the literature for SHIFT$ _N\{x\}$ is $ x(n-N)$, but this can be misunderstood (if $ n$ is not interpreted as `$ \cdot$'), so it will be avoided here. Note that Eq.$ \,$(4.5) can be written on the waveform level instead of the sample level as

$\displaystyle {\cal L}\{$SHIFT$\displaystyle _N\{x\}\}=$SHIFT$\displaystyle _N\{{\cal L}\{x\}\}=$SHIFT$\displaystyle _N\{y\}. \protect$ (5.6)


Order a Hardcopy of Introduction to Digital Filters

Previous: Real Linear Filtering of Complex Signals
Next: Showing Linearity and Time Invariance, or Not

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.


Comments


No comments yet for this page


Add a Comment
You need to login before you can post a comment (best way to prevent spam). ( Not a member? )