Finite-precision arthmetic implementation of DSP systems;
Filter banks and wavelet transform;
Positioning and Navigation systems: GPS, position fixing and dead reckoning techniques;
Laboratory with MATLAB.
F.Argenti,L.Mucchi,E. Del Re, "Elaborazione numerica dei segnali. Teoria, esercizi ed esempi al calcolatore", McGraw-Hill, Milano, 2011.
Paul D. Groves, "Principles of GNSS, Inertial, and Multisensor integrated Navigation systems", Artech House, London 2013.
A.V. Oppenheim, R.W. Schafer, Discrete-time signal processing, Prentice-Hall, 1989.
J.G. Proakis, D.G. Manolakis, Digital signal processing. Principles, algorithms and applications, Prentice-Hall, 1996.
C.S. Burrus et al., Computer-based exercises for signal processing using MATLAB, Prentice-Hall, 1994.
Knowledge to be acquired:
- Performance evaluation and design of finite-precision arithmetic implementation of DSP systems;
- Design of advanced DSP multirate systems;
Knowledge about filter bank theory;
- Introduction to GPS system and to the position fixing and dead reckoning techniques.
Fondamenti di elaborazione numerica dei segnali (Fundamentals of digital signal processing)
The written exam is composed of 3 or 4 exercises and allows to verify the ability to:
design spectrum estimation systems and digital filters, taking into account the constraints that are given by the finite-precision arithmetic;
design multiratesystems, with single or multiple stage implementation, and multiplexing and demultiplexing blocks;
apply filter banks and wavelet transform theory into problem of signal analysis and classification;
describe the main features of the positioning and localization systems.
The oral exam will assess the overall knowledge of the topics that are dealt with in the course; particular attention will
be given to the evaluation criteria of the solution in terms of complexity, cost, robustness and efficiency and to the advanced applications of digital signal processing and localization systems.
The student can submit a MATLAB exercise 2 days before the oral exam, which will be evaluated together with the written and oral exam. The MATLAB exercise can be assigned at the end of the written exam (and not later).
The MATLAB exercise aims at verifying the ability to successfully deal with problems that are typical of digital signal processing and to express in written form the motivations, implementations and results of the elaborate.
Finite-precision arithmetic realization effects
FFT: coefficient quantization, quantization of arithmetic operations. Signal-to-error output ratio.
FIR: finite-precision arithmetic realization structures. Coefficient quantization, quantization of arithmetic operations. Scaling factor. Signal-to-error output ratio.
IIR: finite-precision arithmetic realization structures. Coefficient quantization, quantization of arithmetic operations. Scaling factor. Cascaded second-order sections: poles and zeros association and ordering. Signal-to-error output ratio.
Interpolation and decimation of digital signals: integer factor and rational factor.
Digital frequency conversion by interpolation and decimation.
Filter design for interpolation and decimation. Realization structures for decimators and interpolators. Poliphase structures. CIC filter structures.
Multistage implementation of decimation and interpolation operations.
Filter banks and wavelet transform
Two-channel filter banks. M channels and cosine-modulated bank.
Continuos wavelet transform. Multiresolution analysis. Discrete wavelet transform.
Introduction to Compression and Classification of Data.
Positioning and Navigation systems: GPS, position fixing and dead reckoning techniques