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---
*Verantwortlich:* Prof. Dr.-Ing. Harald Elders-Boll

---++ Lehrveranstaltung
---+++ Befriedigt Modul (MID)
   * aktuelle
      * [[MaCSN2012_DSP]]
      * [[MaTIN2012_DSP]]

---+++ Organisation
<sticky>
  <table border="0">
    <tr valign="top">
      <td>
        <table border="1" cellpadding="2" cellspacing="0">
          <th colspan="2">Version</th>
          <tr>
            <td>erstellt</td>
            <td>2013-04-25</td>
          </tr>
          <tr>
            <td>VID</td>
            <td>2</td>
          </tr>
          <tr>
            <td>gültig ab</td>
            <td>WS 2012/13</td>
          </tr>
          <tr>
            <td>gültig bis</td>
            <td/>
          </tr>
        </table>
      </td>
      <td>         </td>
      <td>
        <table border="1" cellpadding="2" cellspacing="0">
          <th colspan="2">Bezeichnung</th>
          <tr>
            <td>Lang</td>
            <td>%FORMFIELD{"Bezeichnung"}%</td>
          </tr>
          <tr>
            <td>LVID</td>
            <td>F07_DSP</td>
          </tr>
          <tr>
            <td>LVPID (Prüfungsnummer)</td>
            <td/>
          </tr>
        </table>
      </td>
    </tr>
  </table>
</sticky><sticky>
  <table border="0">
    <tr valign="top">
      <td>
        <table border="1" cellpadding="2" cellspacing="0">
          <th colspan="2">Semesterplan (SWS)</th>
          <tr>
            <td>Vorlesung</td>
            <td>%FORMFIELD{"VorlesungSWS"}%</td>
          </tr>
          <tr>
            <td>Übung (ganzer Kurs)</td>
            <td>%FORMFIELD{"UebungGanzSWS"}%</td>
          </tr>
          <tr>
            <td>Übung (geteilter Kurs)</td>
            <td>%FORMFIELD{"UebungHalbSWS"}%</td>
          </tr>
          <tr>
            <td>Praktikum</td>
            <td>%FORMFIELD{"PraktikumSWS"}%</td>
          </tr>
          <tr>
            <td>Projekt</td>
            <td>%FORMFIELD{"ProjektSWS"}%</td>
          </tr>
          <tr>
            <td>Seminar</td>
            <td>%FORMFIELD{"SeminarSWS"}%</td>
          </tr>
          <tr>
            <td>Tutorium (freiwillig)</td>
            <td>%FORMFIELD{"TutoriumSWS"}%</td>
          </tr>
        </table>
      </td>
      <td>    </td>
      <td>
        <table border="1" cellpadding="2" cellspacing="0">
          <th colspan="2">Präsenzzeiten</th>
          <tr>
            <td>Vorlesung</td>
            <td>%FORMFIELD{"VorlesungPZ"}%</td>
          </tr>
          <tr>
            <td>Übung (ganzer Kurs)</td>
            <td>%FORMFIELD{"UebungGanzPZ"}%</td>
          </tr>
          <tr>
            <td>Übung (geteilter Kurs)</td>
            <td>%FORMFIELD{"UebungHalbPZ"}%</td>
          </tr>
          <tr>
            <td>Praktikum</td>
            <td>%FORMFIELD{"PraktikumPZ"}%</td>
          </tr>
          <tr>
            <td>Projekt</td>
            <td>%FORMFIELD{"ProjektPZ"}%</td>
          </tr>
          <tr>
            <td>Seminar</td>
            <td>%FORMFIELD{"SeminarPZ"}%</td>
          </tr>
          <tr>
            <td>Tutorium (freiwillig)</td>
            <td>%FORMFIELD{"TutoriumPZ"}%</td>
          </tr>
        </table>
      </td>
      <td>    </td>
      <td>
        <table border="1" cellpadding="2" cellspacing="0">
          <th colspan="2">max. Teilnehmerzahl</th>
          <tr>
            <td>Übung (ganzer Kurs)</td>
            <td>%FORMFIELD{"UebungGanzTeilnehmer"}%</td>
          </tr>
          <tr>
            <td>Übung (geteilter Kurs)</td>
            <td>%FORMFIELD{"UebungHalbTeilnehmer"}%</td>
          </tr>
          <tr>
            <td>Praktikum</td>
            <td>%FORMFIELD{"PraktikumTeilnehmer"}%</td>
          </tr>
          <tr>
            <td>Projekt</td>
            <td>%FORMFIELD{"ProjektTeilnehmer"}%</td>
          </tr>
          <tr>
            <td>Seminar</td>
            <td>%FORMFIELD{"SeminarTeilnehmer"}%</td>
          </tr>
        </table>
      </td>
    </tr>
  </table>
</sticky>

*Gesamtaufwand:* %FORMFIELD{"Gesamtaufwand"}%

---++++ Unterrichtssprache
   * Englisch

---++++ Niveau
   * %FORMFIELD{"Niveau"}%
---++++ Notwendige Voraussetzungen
   * No formal requirements, but students will be expected to be familiar with:
      * Basic Knowledge of Signals and Systems
         * Continuous-Time LTI-Systems and Convolution
         * Fourier-Transform
      * Basic Knowledge of Probability and Random Variables

---++++ Literatur
   * John G. Proakis and Dimitris K. Manolakis. Digital Signal Processing  (4th Edition). Prentice Hall, 2006.
   * Alan V. Oppenheim, Ronald W. Schafer. Discrete-Time Signal Processing (3rd Edition). Prentice Hall, 2007.
   * Vinay Ingle and John Proakis. Digital Signal Processing using MATLAB. Cengage Learning Engineering, 2011. 

---++++ Dozenten
   * Prof.Dr. Harald Elders-Boll



---++++ Wissenschaftliche Mitarbeiter
   * Dipl.-Ing.Martin Seckler

---++++ Zeugnistext
Digital Signal Processing

---+++ Kompetenznachweis
<sticky>
  <table border="1" cellpadding="2" cellspacing="0">
    <th colspan="2">Form</th>
    <tr>
      <td>sMP</td>
      <td>80% (mündliche Prüfung)</td>
    </tr>
  </table>
</sticky>

<sticky>
  <table border="1" cellpadding="2" cellspacing="0">
    <th colspan="2">Aufwand [h]</th>
    <tr>
      <td>sMP</td>
      <td>10</td>
    </tr>
  </table>
</sticky>

*Intervall:* 2-3/Jahr

-----
---++ Lehrveranstaltungselemente

%STARTSECTION{"Vorlesung / Übung"}%
---+++ <u>Vorlesung / Übung</u>

---++++ Lernziele 
---+++++ Lerninhalte (Kenntnisse)
   * Signals, Systems and Digital Signal Processing
      * Basic Elements of DSP Systems
      * Classification of Signals
         * Continuous-Time and Discrete-Time Signals
         * Deterministic and Random Signals
         * Even and Odd Signals
         * Periodic and Aperiodic Signals
         * Energy and Power of Signals
      * Some Fundamental Signals
   * Discrete-Time Linear Time-Invariant Systems
      * Difference Equations
      * Discrete-Time Convolution
      * Unit-Pulse and Impulse Response
      * Basic Systems Properties: Causality, Stability, Memory
   * Ideal Sampling and Reconstruction
      * Ideal Sampling and the Sampling Theorem
      * Aliasing
   * Fourier-Transform of Discrete-Time Signals
      * Eigenfunctions of Discrete-Time LTI Systems
      * Frequency response of Discrete-Time LTI Systems
      * The Fourier-Transform of Discrete-Time Signals
      * Ideal Continuous-Time Filters
   * The z-Transform
      * The Two-sided z-Transform
      * Properties of the z-Transform
      * The Inverse z-Transform
      * Analysis of LTI Systems using the z-Transform
   * Discrete Fourier-Transform
      * Sampling the DTFT
      * The DFT and the Inverse DFT
      * The Fast Fourier Transform
         * Radix-2 FFT Algorithms
      * Linear Convolution Using the FFT
         * Overlap-And-Add
   * Design of Digital Filters
      * Design of FIR Filters
      * Design of IIR Filters
   * Random Signals
      * Review of Probablity and Random Variables
      * Ensemble Averages
      * Correlation Functions
      * Stationary and Ergodic Processes
      * Power Spectral Density
      * Transmission of Random Signals over LTI Systems
   * Advanced Sampling Techniques
      * Quantization and Encoding
      * Sampling of Bandpass Signals
      * Sampling of Random Signals
      * Sample Rate Conversion
         * Sample Rate Reduction by an Integer Factor
         * Sample Rate Increase by an Integer Factor
         * Sample Rate Conversion by a Rational Factor 
      * Oversampling and Noise Shaping
   * Optimum Linear Filters
      * Linear Prediction
      * The Wiener Filter
         * Orthogonality Principle
         * FIR Wiener Filter
         * IIR Wiener Filter
   * Spectrum Estimation
      * The Periodogram
         * Window Functions
      * Eigenanalysis Algorithms
         * MUSIC Algorithm
         * ESPRIT Algorithm

---+++++ Fertigkeiten
   * Students understand the fundamentals of discrete-time signals and systems
   * Students can analyse the frequency content of a given signal using the appropriate Fourier-Transform and methods for spectrum estimation
   * Analysis of discrete-time LTI Systems
      * Students can calculate the output signal via convolution
      * Students can determine the frequency response of a given system
      * Students can characterize a given system in the frequency domain and in the z-domain
   * Implementation of discrete-time LTI systems
      * Students can implement the convolution sum in software
      * Students can implement different structures for IIR systems in software
      * Sudents can use the FFT to implement an FIR system
   * Analyze effects of practical sampling
      * Quantization noise
      * Aliasing
      * Trade-off pros and cons of advanced implementations like noise shaping


---++++ Begleitmaterial 
   * elektronische Vortragsfolien zur Vorlesung (lecture slides as pdf-file)
   * elektronische Übungsaufgabensammlung (list of problems and solutions manual as pdf-files)


---++++ Besondere Voraussetzungen 


---++++ Besondere Literatur 


---++++ Besonderer Kompetenznachweis 
<sticky>
  <table border="1" cellpadding="2" cellspacing="0">
    <th colspan="2">Form</th>
    <tr>
      <td>bK</td>
      <td>2-3 eTests je 20min (je 1x wiederholbar)</td>
    </tr>
    <tr>
      <td>bÜA</td>
      <td>Präsenzübung und Selbstlernaufgaben</td>
    </tr>
  </table>
</sticky>

<sticky>
  <table border="1" cellpadding="2" cellspacing="0">
    <th colspan="2">Beitrag zum LV-Ergebnis</th>
    <tr>
      <td>bK</td>
      <td>20%</td>
    </tr>
    <tr>
      <td>bÜA</td>
      <td>unbenotet</td>
    </tr>
  </table>
</sticky>

*Intervall:* 1/Jahr

%ENDSECTION{"Vorlesung / Übung"}%



%STARTSECTION{"Praktikum"}%
---+++ <u>Praktikum</u>

---++++ Lernziele 
---+++++ Lerninhalte (Kenntnisse)
   * Review of Probablity and Random Variables
      * Moments, Averages and Distribution Functions
   * Random Signals
      * Ensemble Averages
      * Correlation Functions
      * Stationary and Ergodic Processes
      * Power Spectral Density
      * Transmission of Random Signals over LTI Systems
   * Sampling
      * Sampling and coding for speech and/or audio signals

---+++++ Fertigkeiten
   * Analysis of random variables by means of
      * Mean and moments
      * Distribution
   * Analysis of random signals
      * Determine whether a given random signal is stationary or not
      * Analyse whether a random signal contains discrete harmonic components
         * by using the autocorrelation function
         * by using the power spectral density
   * Combatting noise
      * Remove or suppress high-frequency noise from low-pass signals
   * Abilty to trade-off different methods for digital coding of speech and audio signals
   * 
   * Determine the quatization noise and the SNR for different sampling schemes


---++++ Begleitmaterial 
   * elektronische Beschreibung der Praktikums-Versuche (Instructions for lab experiments as pdf-files)


---++++ Besondere Voraussetzungen 


---++++ Besondere Literatur 


---++++ Besonderer Kompetenznachweis 
<sticky>
  <table border="1" cellpadding="2" cellspacing="0">
    <th colspan="2">Form</th>
    <tr>
      <td>bSZ</td>
      <td>Praktikum (Lab Experiments)</td>
    </tr>
  </table>
</sticky>

<sticky>
  <table border="1" cellpadding="2" cellspacing="0">
    <th colspan="2">Beitrag zum LV-Ergebnis</th>
    <tr>
      <td>bSZ</td>
      <td>Voraussetzung für Modulprüfung (prerequisite for final exam)</td>
    </tr>
  </table>
</sticky>

*Intervall:* 1/Jahr

%ENDSECTION{"Praktikum"}%




%ENDSECTION{"no_toc"}%
Topic-Revision: r14 - 11 Jan 2016, GeneratedContent
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