Skip to main content
Engineering LibreTexts

7.4: Deterministic Examples

  • Page ID
    50198
  • \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \) \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)\(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\) \(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\)\(\newcommand{\AA}{\unicode[.8,0]{x212B}}\)

    This probability model applies to any system with mutually exclusive inputs and outputs, whether or not the transitions are random. If all the transition probabilities \(c_{ji}\) are equal to either 0 or 1, then the process is deterministic.

    A simple example of a deterministic process is the \(NOT\) gate, which implements Boolean negation. If the input is 1 the output is 0 and vice versa. The input and output information are the same, \(I = J\) and there is no noise or loss: \(N = L = 0\). The information that gets through the gate is \(M = I\). See Figure 7.7(a).

    A slightly more complex deterministic process is the exclusive or, \(XOR\) gate. This is a Boolean function of two input variables and therefore there are four possible input values. When the gate is represented by

    Screen Shot 2021-05-10 at 11.31.03 PM.png
    (a) \(NOT\) gate
    Screen Shot 2021-05-10 at 11.31.26 PM.png
    (b) \(XOR\) gate

    Figure 7.7: Probability models of deterministic gates

    a circuit diagram, there are two input wires representing the two inputs. When the gate is represented as a discrete process using a probability diagram like Figure 7.7(b), there are four mutually exclusive inputs and two mutually exclusive outputs. If the probabilities of the four inputs are each 0.25, then \(I\) = 2 bits, and the two output probabilities are each 0.5 so \(J\) = 1 bit. There is therefore 1 bit of loss, and the mutual information is 1 bit. The loss arises from the fact that two different inputs produce the same output; for example if the output 1 is observed the input could be either 01 or 10. There is no noise introduced into the output because each of the transition parameters is either 0 or 1, i.e., there are no inputs with multiple transition paths coming from them.

    Other, more complex logic functions can be represented in similar ways. However, for logic functions with n physical inputs, a probability diagram is awkward if \(n\) is larger than 3 or 4 because the number of inputs is 2\(^n\).


    This page titled 7.4: Deterministic Examples is shared under a CC BY-NC-SA 4.0 license and was authored, remixed, and/or curated by Paul Penfield, Jr. (MIT OpenCourseWare) via source content that was edited to the style and standards of the LibreTexts platform; a detailed edit history is available upon request.