PDF Course Catalog Deutsche Version: DSS

Version: 2 | Last Change: 11.09.2019 11:39 | Draft: 0 | Status: vom verantwortlichen Dozent freigegeben

Long name | Discrete Signals and Systems |
---|---|

Approving CModule | DSS_BaET |

Responsible |
Prof. Dr. Harald Elders-Boll
Professor Fakultät IME |

Level | Bachelor |

Semester in the year | summer semester |

Duration | Semester |

Hours in self-study | 60 |

ECTS | 5 |

Professors |
Prof. Dr. Harald Elders-Boll
Professor Fakultät IME |

Requirements | Knowledge of the following mathematical subjects: Trigonometric functions, exponential function, logarithm, complex calculus, integral and differential calculus, series expansion, geometric series, partial fraction expansion. Knowledge of the following physical subjects: Work, power and energy. |

Language | German |

Separate final exam | Yes |

Jens Rainer Ohm und Hans Dieter Lüke, Signalübertragung, Springer, 2014

Martin Meyer, Signalverarbeitung, Springer Vieweg, 2014

Martin Werner, Signale und Systeme, Springer Vieweg, 2008

Bernd Girot u.a., Einführung in die Systemtheorie, Springer Vieweg, 2007

Martin Meyer, Signalverarbeitung, Springer Vieweg, 2014

Martin Werner, Signale und Systeme, Springer Vieweg, 2008

Bernd Girot u.a., Einführung in die Systemtheorie, Springer Vieweg, 2007

In the final exam 40 points can be gained in total, in the two midterm test 5 points can be gained each yielding 10 points in total for the two tests.

Basic Concepts: Classification of signals and systems, stability, causality

LSI Systems: discrete-time convolution, impulse response, stability, causality

Sampling: sampled vs. discrete time signals, sampling theorem, aliasing

DTFT: derivation, properties, calculation of the DTFT, frequency response

z-Transform: derivation, properties, calculation of the inverse z-transform, system function, stability, block diagrams

DFT: derivation, properties, leakage effect

Basics of filter design: principles of FIR and IIR filter design, properties and comparison of FIR and IIR filters

LSI Systems: discrete-time convolution, impulse response, stability, causality

Sampling: sampled vs. discrete time signals, sampling theorem, aliasing

DTFT: derivation, properties, calculation of the DTFT, frequency response

z-Transform: derivation, properties, calculation of the inverse z-transform, system function, stability, block diagrams

DFT: derivation, properties, leakage effect

Basics of filter design: principles of FIR and IIR filter design, properties and comparison of FIR and IIR filters

Assessment of the stability of LSI systems

Calculation of the DTFT and the z-transform and the corresponding inverse transforms

Implementation of FIR systems by programming of the discrete-time convolution

Implementation of basic IIR Systems

Assessment of the characteristics of LSI filters

Calculation of the DTFT and the z-transform and the corresponding inverse transforms

Implementation of FIR systems by programming of the discrete-time convolution

Implementation of basic IIR Systems

Assessment of the characteristics of LSI filters

Type | Attendance (h/Wk.) |
---|---|

Lecture | 2 |

Exercises (whole course) | 2 |

Exercises (shared course) | 0 |

Tutorial (voluntary) | 0 |

keine/none

none

Lecture slides as PDF documents

Tutorial problems with solutions

Old exams with solutions

Tutorial problems with solutions

Old exams with solutions

Two iPython-based labs on digital soignal processing of acoustical signals to apply the methods from the lecture tutorial to practical problems:

1. Discrete-time signals and systems in the time domain:

Programming of the discrete-time convolution to implement FIR filters

Programming of basic recursive (IIR) filters

Assessment of the filter characteristics by hearing acoustical signals

2. Discrete-time signals and systems in the frequency domain:

Analysis of basic FIR and IIR filters in the frequency domain using the DTFTR and the z-transform from Scipy

Comparison of the auditory impression and the frequency response

1. Discrete-time signals and systems in the time domain:

Programming of the discrete-time convolution to implement FIR filters

Programming of basic recursive (IIR) filters

Assessment of the filter characteristics by hearing acoustical signals

2. Discrete-time signals and systems in the frequency domain:

Analysis of basic FIR and IIR filters in the frequency domain using the DTFTR and the z-transform from Scipy

Comparison of the auditory impression and the frequency response

Type | Attendance (h/Wk.) |
---|---|

Practical training | 1 |

Tutorial (voluntary) | 0 |

keine/none

none

Lab instructions as iPython notebooks.

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