1I2AE2 | Digital Signal Processing | Computer Science | S6 | ||||||
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Lessons : 10 h | TD : 9 h | TP : 15 h | Project : 0 h | Total : 34 h | |||||
Co-ordinator : Miloud Frikel |
Prerequisite | |
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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. |
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Syllabus | |
The discrete signals Discrete Fourier Transform principle and "digital" spectrum analyzers Discrete systems Infinite impulse response filters: IIR Filters Filters FIR: FIR filters |
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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 |
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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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