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Discrete-time signals are mathematical entities; in particular, they are functions with an independent time variable and a dependent variable that typically represents some kind of real-world quantity of interest. But as interesting as a signal may be on its own, engineers usually want to do something to it. This kind of action is what discrete-time systems are all about. A discrete-time system is a mathematical transformation that maps a discrete-time input signal (usually designated $x$) into a discrete-time output signal (usually designated $y$). In other words, it takes an input signal and modifies it to produce an output signal:

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System $\mathcal{H}$ takes takes a discrete time signal $x$ as an input and produces an output $y$.
There is no end to the possibilities of what a system could do. Systems might be trivially dull (e.g., produce an output of 0 regardless of the input) or incredibly complex (e.g., isolate a single voice speaking in a crowd). Here are a few examples of systems:
  • A speech recognition system converts acoustic waves of speech into text
  • A radar system transforms the received radar pulse to estimate the position and velocity of targets
  • A functional magnetic resonance imaging (fMRI) system transforms measurements of electron spin into voxel-by-voxel estimates of brain activity
  • A 30 day moving average smooths out the day-to-day variability in a stock price

Signal length and systems

Recall that discrete-time signals can be broadly divided into two classes based upon their length: they are either infinite length or finite length (and recall also that periodic signals, though infinite in length, can be viewed as finite-length signals when we take a single period into account). Likewise, discrete-time systems are also finite or infinite length, depending on the kind of input signals they take. Finite-length systems take in a finite-length input and produce a finite-length output (of the same length), with infinite-length systems doing the same for infinite-length signals.

Examples of discrete-time systems

So a system takes an input signal $x$ and produces an output signal $y$. How does this look, mathematically? Below are several examples of systems and their mathematical expression:
  • Identity: $y[n] = x[n]$
  • Scaling: $y[n] = 2\, x[n]$
  • Offset: $y[n] = x[n]+2$
  • Square signal: $y[n] = (x[n])^2$
  • Shift: $y[n] = x[n+m]\quad m\in Z$ \]
  • Decimate: $y[n] = x[2n]$
  • Square time: $y[n] = x[n^2]$
  • Moving average (combines shift, sum, scale): $y[n] = \frac{1}{2}(x[n]+x[n-1])$
  • Recursive average: $y[n] = x[n]+ \alpha\,y[n-1]$

So systems take input signals and produce output signals. We have seen some examples of systems, and have also introduced a broad categorization of systems as either operating on finite or infinite length signals.

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Source:  OpenStax, Discrete-time signals and systems. OpenStax CNX. Oct 07, 2015 Download for free at https://legacy.cnx.org/content/col11868/1.2
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