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<document xmlns="http://cnx.rice.edu/cnxml" xmlns:m="http://www.w3.org/1998/Math/MathML" xmlns:md="http://cnx.rice.edu/mdml/0.4" xmlns:bib="http://bibtexml.sf.net/" id="m10375">
  
  <name>Homework 3 of Elec 430</name>
  <metadata>
  <md:version>2.8</md:version>
  <md:created>2001/10/05</md:created>
  <md:revised>2004/01/07 10:15:05.746 US/Central</md:revised>
  <md:authorlist>
    <md:author id="aaz">
      <md:firstname>Behnaam</md:firstname>
      
      <md:surname>Aazhang</md:surname>
      <md:email>aaz@ece.rice.edu</md:email>
    </md:author>
  </md:authorlist>

  <md:maintainerlist>
    <md:maintainer id="dinesh">
      <md:firstname>Dinesh</md:firstname>
      
      <md:surname>Rajan</md:surname>
      <md:email>dinesh@ece.rice.edu</md:email>
    </md:maintainer>
    <md:maintainer id="mohammad">
      <md:firstname>Mohammad</md:firstname>
      <md:othername>Jaber</md:othername>
      <md:surname>Borran</md:surname>
      <md:email>mohammad@ece.rice.edu</md:email>
    </md:maintainer>
    <md:maintainer id="aaz">
      <md:firstname>Behnaam</md:firstname>
      
      <md:surname>Aazhang</md:surname>
      <md:email>aaz@ece.rice.edu</md:email>
    </md:maintainer>
    <md:maintainer id="mrshawn">
      <md:firstname>Shawn</md:firstname>
      
      <md:surname>Stewart</md:surname>
      <md:email>mrshawn@alumni.rice.edu</md:email>
    </md:maintainer>
    <md:maintainer id="rha">
      <md:firstname>Roy</md:firstname>
      
      <md:surname>Ha</md:surname>
      <md:email>rha@rice.edu</md:email>
    </md:maintainer>
  </md:maintainerlist>
  
  <md:keywordlist>
    <md:keyword>homework</md:keyword>
  </md:keywordlist>

  <md:abstract>(Blank Abstract)</md:abstract>
</metadata>



  <content>
    
    <exercise id="prob1">
      <problem>
	<para id="prob1para1">
        Suppose that a white Gaussian noise
        <m:math display="inline">
          <m:ci>
            <m:msub>
              <m:mi>X</m:mi>
              <m:mi>t</m:mi>
            </m:msub>
          </m:ci>
        </m:math>
        is input to a linear system with transfer function given by
        <equation id="prob1eq1">
          <m:math display="block">
            <m:apply>
              <m:eq/>
                <m:apply>
                  <m:ci type="fn">H</m:ci>
                  <m:ci>f</m:ci>
                </m:apply>
                <m:piecewise>
                  <m:piece>
                    <m:cn>1</m:cn>
                    <m:apply>
                      <m:leq/>
                        <m:apply>
                          <m:abs/>
                            <m:ci>f</m:ci>
                        </m:apply>
                        <m:cn>2</m:cn>
                    </m:apply>
                  </m:piece>
                  <m:piece>
                    <m:cn>0</m:cn>
                    <m:apply>
                      <m:gt/>
                        <m:apply>
                          <m:abs/>
                            <m:ci>f</m:ci>
                        </m:apply>
                        <m:cn>2</m:cn>
                    </m:apply>
                  </m:piece>
                </m:piecewise>
            </m:apply>
          </m:math>
        </equation>
        Suppose further that the input process is zero mean and has spectral
        height
        <m:math display="inline">
          <m:apply>
            <m:eq/>
              <m:apply>
                <m:divide/>
                  <m:ci>
                    <m:msub>
                      <m:mi>N</m:mi>
                      <m:mn>0</m:mn>
                    </m:msub>
                  </m:ci>
                  <m:cn>2</m:cn>
              </m:apply>
              <m:cn>5</m:cn>
          </m:apply>
        </m:math>.
        Let
        <m:math display="inline">
          <m:ci>
            <m:msub>
              <m:mi>Y</m:mi>
              <m:mi>t</m:mi>
            </m:msub>
          </m:ci>
        </m:math>
        denote the resulting output process.
      </para>
      
	<list id="prob1parta" type="enumerated">
         <item>Find the power spectral density of
            <m:math display="inline">
              <m:ci>
                <m:msub>
                  <m:mi>Y</m:mi>
                  <m:mi>t</m:mi>
                </m:msub>
              </m:ci>
            </m:math>.
            Find the autocorrelation of
            <m:math display="inline">
	      <m:ci>
	        <m:msub>
	          <m:mi>Y</m:mi>
	          <m:mi>t</m:mi>
	        </m:msub>
	      </m:ci>
            </m:math> (<foreign>i.e.</foreign>,
            <m:math display="inline">
              <m:apply>
              <m:ci type="fn">
                <m:msub>
                  <m:mi>R</m:mi>
                  <m:mi>Y</m:mi>
                </m:msub>
              </m:ci>
              <m:ci>τ</m:ci>
              </m:apply>
            </m:math>).
       </item>
       
       <item>
         Form a discrete-time process (that is a sequence of
            random variables) by sampling
            <m:math display="inline">
              <m:ci>
                <m:msub>
                  <m:mi>Y</m:mi>
                  <m:mi>t</m:mi>
	      </m:msub>
	    </m:ci>
	  </m:math>
	  at time instants <m:math><m:ci>T</m:ci> </m:math> seconds
	  apart. Find a value for <m:math><m:ci>T</m:ci> </m:math>
	  such that these samples are uncorrelated.  Are these samples
	  also independent?
	</item>
	
	<item>
	  What is the variance of each sample of the output process?
	</item>
      </list>
	<figure id="prob1fig" orient="horizontal">
        <media type="image/png" src="HW3Fig1.png"/>
      </figure>
      </problem>
    </exercise>
    
    <exercise id="prob2">
      <problem>
      
      <para id="prob2para1">
        Suppose that
        <m:math display="inline">
          <m:ci>
            <m:msub>
              <m:mi>X</m:mi>
              <m:mi>t</m:mi>
            </m:msub>
          </m:ci>
        </m:math>
        is a zero mean white Gaussian process with spectral height
        <m:math display="inline">
          <m:apply>
            <m:eq/>
              <m:apply>
                <m:divide/>
                  <m:ci>
                    <m:msub>
                      <m:mi>N</m:mi>
                      <m:mn>0</m:mn>
                    </m:msub>
                  </m:ci>
                  <m:cn>2</m:cn>
              </m:apply>
              <m:cn>5</m:cn>
          </m:apply>
        </m:math>.  Denote
        <m:math display="inline">
          <m:ci>
            <m:msub>
              <m:mi>Y</m:mi>
              <m:mi>t</m:mi>
            </m:msub>
          </m:ci>
        </m:math>
        as the output of an integrator when the input is
        <m:math display="inline">
           <m:ci>
             <m:msub>
               <m:mi>Y</m:mi>
               <m:mi>t</m:mi>
             </m:msub>
           </m:ci>
        </m:math>.
      </para>
      
      <figure id="prob2fig">
        <media type="image/png" src="HW3Fig2.png"/>
      </figure>
      
      <list id="prob2list" type="enumerated">
        <item>Find the mean function of
          <m:math display="inline">
	    <m:ci>
	      <m:msub>
	        <m:mi>Y</m:mi>
	        <m:mi>t</m:mi>
	      </m:msub>
	    </m:ci>
          </m:math>. Find the autocorrelation function of
          <m:math display="inline">
            <m:ci>
              <m:msub>
                <m:mi>Y</m:mi>
                <m:mi>t</m:mi>
              </m:msub>
            </m:ci>
          </m:math>,
          <m:math display="inline">
            <m:apply>
              <m:ci type="fn">
                <m:msub>
                  <m:mi>R</m:mi>
                  <m:mi>Y</m:mi>
                </m:msub>
              </m:ci>
              <m:apply>
                <m:plus/>
                  <m:ci>t</m:ci>
                  <m:ci>τ</m:ci>
              </m:apply>
              <m:ci>t</m:ci>
            </m:apply>
          </m:math>
        </item>
        <item>Let
          <m:math display="inline">
            <m:ci>
              <m:msub>
                <m:mi>Z</m:mi>
                <m:mi>k</m:mi>
              </m:msub>
            </m:ci>
          </m:math>
          be a sequence of random variables that have been obtained by
          sampling
          <m:math display="inline">
            <m:ci>
              <m:msub>
                <m:mi>Y</m:mi>
                <m:mi>t</m:mi>
              </m:msub>
            </m:ci>
          </m:math>
          at every <m:math><m:ci>T</m:ci> </m:math> seconds and
	  dumping the samples, that is
          <equation id="prob3eq">
            <m:math display="block">
              <m:apply>
                <m:eq/>
                  <m:ci>
                    <m:msub>
                      <m:mi>Z</m:mi>
                      <m:mi>k</m:mi>
                    </m:msub>
                  </m:ci>
                  <m:apply>
                    <m:int/>
                      <m:bvar><m:ci>τ</m:ci></m:bvar>
                      <m:lowlimit>
                        <m:apply>
                          <m:times/>
                            <m:apply>
                              <m:minus/>
                                <m:ci>k</m:ci>
                                <m:cn>1</m:cn>
                            </m:apply>
                            <m:ci>T</m:ci>
                        </m:apply>
                      </m:lowlimit>
                      <m:uplimit>
                        <m:apply>
                          <m:times/>
                            <m:ci>k</m:ci>
                            <m:ci>T</m:ci>
                        </m:apply>
                      </m:uplimit>
                      <m:ci>
                        <m:msub>
                          <m:mi>X</m:mi>
                          <m:mi>τ</m:mi>
                        </m:msub>
                      </m:ci>
                  </m:apply>
              </m:apply>
            </m:math>
          </equation>
          Find the autocorrelation of the discrete-time processes
          <m:math display="inline">
            <m:ci>
              <m:msub>
                <m:mi>Z</m:mi>
                <m:mi>k</m:mi>
              </m:msub>
            </m:ci>
          </m:math>'s, that is,
          <m:math display="inline">
            <m:apply>
              <m:eq/>
                <m:apply>
                  <m:ci type="fn">
                    <m:msub>
                      <m:mi>R</m:mi>
                      <m:mi>Z</m:mi>
                    </m:msub>
                  </m:ci>
                  <m:apply>
                    <m:plus/>
                      <m:ci>k</m:ci>
                      <m:ci>m</m:ci>
                  </m:apply>
                  <m:ci>k</m:ci>
                </m:apply>
                <m:apply>
                  <m:ci type="fn">E</m:ci>
                  <m:apply>
                    <m:times/>
                      <m:ci>
                        <m:msub>
                          <m:mi>Z</m:mi>
                          <m:mi>k+m</m:mi>
                        </m:msub>
                      </m:ci>
                      <m:ci>
                        <m:msub>
                          <m:mi>Z</m:mi>
                          <m:mi>k</m:mi>
                        </m:msub>
                      </m:ci>
                  </m:apply>
                </m:apply>
            </m:apply>
          </m:math>
        </item>
        <item>Is
          <m:math display="inline">
            <m:ci>
              <m:msub>
                <m:mi>Z</m:mi>
                <m:mi>k</m:mi>
              </m:msub>
            </m:ci>
          </m:math>
          a wide sense stationary process?
        </item>
      </list>
      </problem>
    </exercise>
    
    <exercise id="prob4">
      <problem>
      <para id="prob4para">
        <cite>Proakis and Salehi</cite>, problem 3.63, parts 1, 3, and 4
      </para>
      </problem>
    </exercise>
    
    <exercise id="prob5">
      <problem>
      <para id="prob5para">
        <cite>Proakis and Salehi</cite>, problem 3.54
      </para>
      </problem>
    </exercise>
    
    <exercise id="prob6">
      <problem>
      <para id="prob6para">
        <cite>Proakis and Salehi</cite>, problem 3.62
      </para>
      </problem>
    </exercise>
    
  </content>				      
  
</document>
