{"id":1433,"date":"2019-12-04T22:09:00","date_gmt":"2019-12-05T06:09:00","guid":{"rendered":"https:\/\/linearcontrol.info\/fundamentals\/?p=1433"},"modified":"2019-12-06T20:53:56","modified_gmt":"2019-12-07T04:53:56","slug":"discrete-time-systems-and-the-z-transform-part-i","status":"publish","type":"post","link":"https:\/\/linearcontrol.info\/fundamentals\/index.php\/2019\/12\/04\/discrete-time-systems-and-the-z-transform-part-i\/","title":{"rendered":"Discrete-time systems and the Z-transform. Part I"},"content":{"rendered":"\n<p>The Z-transform does to discrete-time signals and systems what the Laplace transform does to a continuous-time signals and systems. <\/p>\n\n\n\n<!--more-->\n\n\n\n<h2>The Z-transform<\/h2>\n\n\n\n<p>The Z-transform of the discrete-time signal $u[n]$, $n \\in \\mathbb{N}$, is the function of the complex variable $z$ defined by<\/p>\n\n\n\n<p>$$U[z]=\\mathcal{Z} \\{ u[n] \\} = \\sum_{n=0}^{\\infty} u[n] \\, z^{-n}.$$ <\/p>\n\n\n\n<p> As with the Laplace transform, $u[n]$ is assumed to be zero for negative $n$, that is $u[n] = 0$, $n &lt; 0$.<\/p>\n\n\n\n<p>Exponential discrete-time signals are of great importance and the calculation<\/p>\n\n\n\n<p>$$<br>\\mathcal{Z}\\{ a^{n} \\} =  \\sum_{n=0}^{\\infty} a^n \\, z^{-n} = \\frac{1}{1 &#8211; a z^{-1}}, \\quad |z|&gt;|a|. <br>$$<\/p>\n\n\n\n<p>reveals many of the inner workings of the Z-transform. The Z-transform of the exponential has a domain of convergence which is the exterior of the disc of radius $|a|$. As with the Laplace transform, the Z-transform has no trouble handling unbounded signals, e.g. $|a| &gt; 1$, by adapting its region of convergence.<\/p>\n\n\n\n<p>A sufficient condition for a discrete-time signal to admit a Z-transform is for it to be of exponential order, that is if there exists $a &gt; 0$, and $M &gt; 0$ such that<\/p>\n\n\n\n<p> $$|u[n]| \\leq M a^n, \\quad n \\in \\mathbb{N}.$$<\/p>\n\n\n\n<p>Indeed, with $z = r e^{j \\theta}$<\/p>\n\n\n\n<p> $$|U[z]|\\leq \\sum_{n=0}^{\\infty} |u[n]| \\, |z^{-n}| \\leq  M \\sum_{n=0}^{\\infty} a^n \\, r^{-n} = \\frac{1}{1 + a r^{-1}}$$<\/p>\n\n\n\n<p>is bounded for all $r &gt; a$. The region of convergence of a typical Z-transform is the exterior of a disc centered at the origin, whereas the region of convergence of a Laplace transform were a right half-plane. <\/p>\n\n\n\n<p>The Z-transform has many properties that are analogous to the properties of the Laplace transform. For example, one useful property is the delay property<\/p>\n\n\n\n<p>$$\\mathcal{Z} \\{ u[n-k] \\} = z^{-k} U[z], \\quad k \\geq 0,$$<\/p>\n\n\n\n<p>obtained by assuming $u[n] = 0$, $n &lt; 0$, and changing indices as in <\/p>\n\n\n\n<p> $$\\mathcal{Z} \\{ u[n-k] \\} = \\sum_{n=0}^{\\infty} u[n-k] \\, z^{-n} =  \\sum_{m=-k}^{\\infty} u[m] \\, z^{-m-k} =z^{-k} U[z].$$<\/p>\n\n\n\n<p>As discussed <a href=\"https:\/\/linearcontrol.info\/fundamentals\/index.php\/2019\/12\/06\/sampling-part-iii\">in this post<\/a>, the inverse Z-transform is given by the integral formula<\/p>\n\n\n\n<p> $$<br>u[n]=\\frac{1}{2 \\pi j} \\oint_{C} U[z] \\, z^{n-1} \\, dz, <br>$$<\/p>\n\n\n\n<p>a formula that is rarely used in practice, but of great theoretical importance.<\/p>\n\n\n\n<p>We shall discuss other properties of the Z-transform in more detail later in this and on future posts.<\/p>\n\n\n\n<h2>Discrete-time linear systems, impulse response and convolution<\/h2>\n\n\n\n<p>As with continuous-time systems, discrete-time systems are completely described by one signal: the impulse response $g[n]$. The key ingredient is once again the definition of a suitable impulse<\/p>\n\n\n\n<p>$$<br>\\delta[n] = \\begin{cases} 1, &amp; n = 0 \\\\ 0, &amp; n \\neq 0 \\end{cases}<br>$$<\/p>\n\n\n\n<p>Note how a discrete-time impulse is much better behaved than its continuous-time counterpart: the discrete-time impulse is actually a true signal!<\/p>\n\n\n\n<p>As discussed <a href=\"https:\/\/linearcontrol.info\/fundamentals\/index.php\/2019\/11\/09\/the-impulse-response\/\">here<\/a> and in Chapter 3 in the case of continuous-time systems, with the help of the impulse one can represent signals as a combination of delayed impulses<\/p>\n\n\n\n<p>$$<br>u[n] = \\sum_{k=-\\infty}^{\\infty} u[k] \\, \\delta[n &#8211; k]<br>$$<\/p>\n\n\n\n<p>and the response of an arbitrary  discrete-time linear time-invariant system by the convolution<\/p>\n\n\n\n<p> $$<br>y[n] = \\sum_{k=-\\infty}^{\\infty} g[n &#8211; k] \\, u[k] = \\sum_{k=-\\infty}^{\\infty} g[k] \\, u[n &#8211; k].<br>$$<\/p>\n\n\n\n<p>With causality, in which case $u[n]$ and $g[n]$ are zero when $n &lt; 0$, these reduce to<\/p>\n\n\n\n<p>$$<br>y[n] = \\sum_{k=0}^{n} g[n &#8211; k] \\, u[k] = \\sum_{k=0}^{n} g[k] \\, u[n &#8211; k]<br>$$ <\/p>\n\n\n\n<p>as for causal continuous-time systems.<\/p>\n\n\n\n<p>One of the most useful properties of the Z-transform is the ability to transform a convolution into a product as in<\/p>\n\n\n\n<p> $$<br>\\begin{aligned}<br>Y[z]=\\mathcal{Z}\\{y[n]\\} &amp;= \\sum_{n=0}^{\\infty} \\sum_{k=0}^{\\infty} g[k] \\, u[n-k] \\, z^{-n} \\\\<br>&amp;= \\sum_{k=0}^{\\infty} g[k]  \\sum_{n=0}^{\\infty}  u[n-k] \\, z^{-n} \\\\ <br>&amp;= \\sum_{k=0}^{\\infty} g[k]  z^{-k} U[z]  \\\\<br>&amp;= G[z] \\, U[z] <br> \\end{aligned}<br>$$ <\/p>\n\n\n\n<p>after using the delay property of the Z-transform. One can recognize in the above formula the discrete-time transfer-function $G[z]=\\mathcal{Z}\\{g[n]\\}$.<\/p>\n\n\n\n<p>The continuous- versus discrete-time analogies go well beyond those discussed so far. We will leave some of those for future posts.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The Z-transform does to discrete-time signals and systems what the Laplace transform does to a continuous-time signals and systems.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false},"categories":[7],"tags":[15,19,59],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/linearcontrol.info\/fundamentals\/index.php\/wp-json\/wp\/v2\/posts\/1433"}],"collection":[{"href":"https:\/\/linearcontrol.info\/fundamentals\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/linearcontrol.info\/fundamentals\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/linearcontrol.info\/fundamentals\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/linearcontrol.info\/fundamentals\/index.php\/wp-json\/wp\/v2\/comments?post=1433"}],"version-history":[{"count":26,"href":"https:\/\/linearcontrol.info\/fundamentals\/index.php\/wp-json\/wp\/v2\/posts\/1433\/revisions"}],"predecessor-version":[{"id":1652,"href":"https:\/\/linearcontrol.info\/fundamentals\/index.php\/wp-json\/wp\/v2\/posts\/1433\/revisions\/1652"}],"wp:attachment":[{"href":"https:\/\/linearcontrol.info\/fundamentals\/index.php\/wp-json\/wp\/v2\/media?parent=1433"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/linearcontrol.info\/fundamentals\/index.php\/wp-json\/wp\/v2\/categories?post=1433"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/linearcontrol.info\/fundamentals\/index.php\/wp-json\/wp\/v2\/tags?post=1433"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}