Learning objectives
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This course aims at exploring the design and application aspects of Digital Signal Processing, whose most common exploitation area is in the processing of audio and video signals.<br />
The organization of both the contents and the teaching method has two distinctive features: the contents are enriched, year after year,with advanced application topics, also thanks to the fundamental contribution of the students; as for the teaching method, half of the time is spent in the laboratory, applying the techniques discussed in class to digital signals acquired on a PC, through the numerical software Matlab.
Prerequisites
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For this course, it is assumed that the student has already taken a first course in Digital Signal Processing ("Elaborazione Numericadei Segnali A", at Parma University).
Course unit content
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DESIGN OF DIGITAL FILTERS<br />
Relationship between difference equations, block diagrams and flow graphs. Structures for Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filters: direct forms, cascade and parallel forms; transposed forms; structures for linear phase FIR filters.<br />
Design methods for digital filters: specifications, choice of the response type, coefficients calculation and realization structure.<br />
Synthesis of IIR filters from analog filters: review of Butterworth and Chebychev analog filters; pole-zero placing; the impulse invariance method; the matched Z transform; the bilinear transformation method.<br />
Synthesis of linear phase FIR filters: the windowing method; the Kaiser window method; the optimal (equiripple) method: the alternation theorem and the Parks-McClellan algorithm; the frequency sampling method.<br />
SPECTRAL ANALYSIS AND ESTIMATION<br />
Spectral estimation of stationary signals: the periodogram. Frequency resolution and Leakage. Spectral estimation of nonstationary signals: the time-varying DFt and the spectrogram. Applications to the analysis of speech signals.<br />
THE DISCRETE COSINE TANSFORM (DCT)<br />
Definitions and inverse Transforms: the DCT-1 and DCT-2. Energy compaction property. Applications to image compression.<br />
SPEECH SIGNAL MODELS<br />
Review of acoustic phonetics and the acoustic theory of speech production; digital models for speech signals. Analysis and synthesis of speech signals. Pitch freeuqncy and formant frequencies. The VOCODER model and its variations.<br />
LINEAR PREDICTIVE CODING (LPC)<br />
AR and MA filters; predictive filter with impulsive or noise input. Calculation of the Error signal power and its minimization. Yule-Walker equations. Interpretation in the frequency domain: predictive filter as a spectral estimator. Applications to speech signals.
Full programme
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Bibliography
A. V. Oppenheim, R. W. Schafer, J. R. Buck, "Discrete-Time Signal Processing, 2nd Ed.", Prentice-Hall, 1999.
Teaching methods
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Assessment is based on an oral exam and on the production of a brief essay - either an application project or a research on an advanced topic - carried out by students organized in small groups (two to four).<br />
Assessment methods and criteria
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Other information
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