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Digital Signal Processing

1I2AE2 Digital Signal Processing Computer Science S6
Lessons : 10 h TD : 9 h TP : 15 h Project : 0 h Total : 34 h
Co-ordinator : Miloud Frikel
Prerequisite
Signal processing, Applied Mathematics.
Course Objectives
Acquire basic knowledge for modeling, representation and processing of discrete signals. After an introduction to digital deterministic signal processing, we give the basic results of the concept of sampling to deal with a comprehensive way the representation of discrete systems, namely the difference equations, impulse response and time and frequency properties that result. Modeling of signals is then deduced in a natural way. Then are discussed the more specific to digital signals such as the Fourier transform of a discrete-time signal and discrete Fourier transform. The stability properties are established and illustrated before processing the synthesis of digital filters.
Syllabus
The discrete signals
Discrete Fourier Transform principle and "digital" spectrum analyzers
Discrete systems
Infinite impulse response filters: IIR Filters
Filters FIR: FIR filters
Practical work (TD or TP)
The labs can better understand the problems of digital signal processing, including aspects of sampling, spectral analysis and filtering. Applications will be carried out with Matlab and Simulink:
Sampling signax and discrete Fourier transform (DFT)
Filter discrete recurrence equation
Implementation of digital filtering to remove the parasite Sound
Codes DTMF (dual tone multi-frequency): Detection by the Goertzel algorithm
Acquired skills
Usual techniques of digital signal processing: acquisition, analysis and filtering.
Bibliography
M. Bellanger, Digital Signal Processing Theory and Practice, Wiley, 2006. M. Kunt, Digital Signal Processing, Wiley, 1981.
A. Oppenheim and R. Shafer, Digital Signal Processing, Prentice Hall, 1975.

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