PDF Course Catalog Deutsche Version: SIG

Version: 4 | Last Change: 20.05.2021 16:12 | Draft: 0 | Status: vom verantwortlichen Dozent freigegeben

Long name | Signal Processing |
---|---|

Approving CModule | SIG_BaTIN |

Responsible |
Prof. Dr. Rainer Bartz
Professor Fakultät IME |

Level | Bachelor |

Semester in the year | winter semester |

Duration | Semester |

Hours in self-study | 78 |

ECTS | 5 |

Professors |
Prof. Dr. Rainer Bartz
Professor Fakultät IME |

Requirements | elementary functions (polynomial, rational, trigonometric, exponential functions); sequences and series, limits, l'Hospital; polynomial division, partial fraction expansion; systems of linear equations; complex calculus, complex-valued functions, polar and cartesian representation, Euler's formulas; basic programming skills (C preferred); constants, variables, functions, arrays; data types, loops, if..else; structures, arrays of structures; bitwise operators; dada type conversion, registers, number representations; realtime processing; compiler, linker, debugger |

Language | German |

Separate final exam | Yes |

Carlson, G. E.: Signal and Linear System Analysis, John Wiley & Sons, Inc.

basic concepts (signal, system, characteristics)

signals:

discrete time reference signals (impulse, step, ...) and their characteristics

Fourier series of discrete-time signals

z-transform of discrete-time signals

systems; especially discrete-time (DT) LTI sytems

signal transmission

difference equations and block diagrams

DT convolution

recursive numerical approach

z-transform of a delay element

the z-transfer function

responses on reference signals

general system responses

pole-zero plot and stability

canonical system structures: DF1, DF2

FIR and IIR filter systems; comparison

signals:

discrete time reference signals (impulse, step, ...) and their characteristics

Fourier series of discrete-time signals

z-transform of discrete-time signals

systems; especially discrete-time (DT) LTI sytems

signal transmission

difference equations and block diagrams

DT convolution

recursive numerical approach

z-transform of a delay element

the z-transfer function

responses on reference signals

general system responses

pole-zero plot and stability

canonical system structures: DF1, DF2

FIR and IIR filter systems; comparison

students acquire fundamental knowledge on theory and applications of discrete-time signals and systems

they understand the behavior of typical systems

they can apply algorithms for convolution, z-transform, and others

they are able to understand a system model, and to analyze it in time and frequency domain

they can apply system theory to real-world systems

students can implement a discrete-time system based on given requirements

they understand the behavior of typical systems

they can apply algorithms for convolution, z-transform, and others

they are able to understand a system model, and to analyze it in time and frequency domain

they can apply system theory to real-world systems

students can implement a discrete-time system based on given requirements

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

Lecture | 2 |

Exercises (whole course) | 1 |

Exercises (shared course) | 0 |

Tutorial (voluntary) | 0 |

keine/none

Requirements are documented by MA1, PI1, MA2, GSP.

compendium with all relevant contents is available (English language)

some additional presentation slides electronically available

exercises and solutions electronically available (German language)

some additional presentation slides electronically available

exercises and solutions electronically available (German language)

none

sampling input and output signals of a continuous-time (CT) system

basic algorithms of signal processing

software implementation of a DT system from a requirements specification

basic algorithms of signal processing

software implementation of a DT system from a requirements specification

students can use state of the art tools for system simulation, and implementation

they understand the relationship between CT and DT systems and can explain the most important effects

students are able to solve problems in small teams

they can implement basic algorithms for signal processing

- based on Matlab scripts

- on a DSP platform (Texas Instruments C6713 with Code Composer Studio)

they understand the relationship between CT and DT systems and can explain the most important effects

students are able to solve problems in small teams

they can implement basic algorithms for signal processing

- based on Matlab scripts

- on a DSP platform (Texas Instruments C6713 with Code Composer Studio)

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

Practical training | 1 |

Tutorial (voluntary) | 0 |

keine/none

Requirements are documented by MA1, PI1, MA2, GSP.

introduction to the lab components electronically available

specification of the lab tasks electronically available

documentation on the tools and software environments electronically available

specification of the lab tasks electronically available

documentation on the tools and software environments electronically available

none

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