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Digital signal processing and mathematics 4 (Spring 2006)

Course code : EDSM4-U01
ECTS Credits : 10 Status : Compulsory
Placement : 4. semester Hours per week : 8
Length : 1 semester Teaching Language : English if English students are present
Principal Content : The main content is divided into three parts: A, B, C and D:
A. Discrete time Fourier analysis: Discrete time Fourier transform (DTFT) and inverse (IDTFT). Discrete Fourier transform (DFT/FFT) and inverse (IDFT/IFFT). Practical spectral analysis: Spectrum analysers, frequency resolution, amplitude precision, window functions, leakage, zero padding.

B. Probability and signals: Probability: definitions, calculus and Probability functions. Stochastic Signals. Elementary Information Theory and Source Coding.

C. Speech Coding in telecommunication: Quantization noise, linear Pulse Code Modulation (PCM) and companding. Differential PCM (DPCM) and linear prediction, adaptive DPCM (ADPCM), Pitch-excited linear predictictive coding (LPC). Modern speech coding principles and standards (GSM etc).

D. Automatic Speech Recognition: Cepstrum Analysis, Feature Extraction, Time Warping, Model word production, Distance computation and word recognition.
Teaching method : In the beginning of the semester the teaching will be a mixture of classroom lecturing and problem work solving, partly based on MATLAB as the simulation tool. This form makes up 50% to 75% of the scheduled time in the semester, distributed as 100% in the beginning of the semester and 0% towards the end of the semester. In relation to the contents items A and B two large course assignments have to be carried out and documented in writing. In relation to the contents item C and D a large course assignment involving design of a speech recognizer has to be carried out and documented in a report.
Required prequisites : Documented knowledge similar to DSM2
Responsible teacher : Anne Marie Hinke , amh@ihk.dk