ITA | ENG
B010462 - FUNDAMENTALS OF DIGITAL SIGNAL PROCESSING
Main information
Teaching Language
Course Content
Suggested readings
Learning Objectives
Prerequisites
Teaching Methods
Further information
Type of Assessment
Course program
Academic Year 2015-16
Coorte 2015 - Second Cycle Degree in ELECTRONICS ENGINEERING
Course year
First year - First Semester
Belonging Department
Information Engineering (DINFO)
Course Type
Single education field course
Scientific Area
ING-INF/03 - TELECOMMUNICATIONS
Credits
6
Teaching Hours
48
Teaching Term
21/09/2015 ⇒ 18/12/2015
Attendance required
No
Type of Evaluation
Final Grade
Course Content
show
Course program
show
Lectureship
Mutuality
Course teached as:
B010462 - FONDAMENTI DI ELABORAZIONE NUMERICA DEI SEGNALI
3-years First Cycle Degree (DM 270/04) in ELECTRONICS AND TELECOMMUNICATIONS ENGINEERING
B010462 - FONDAMENTI DI ELABORAZIONE NUMERICA DEI SEGNALI
3-years First Cycle Degree (DM 270/04) in ELECTRONICS AND TELECOMMUNICATIONS ENGINEERING
Teaching Language
Italian
Course Content
Digital signal representation
Discrete linear time-invariant systems
Discrte Fourier transform
Design of finite impulse response filters
Design of infinite impulse response filters
Implemetation of gigital signal processing systems
Applications and laboratory with MATLAB
Discrete linear time-invariant systems
Discrte Fourier transform
Design of finite impulse response filters
Design of infinite impulse response filters
Implemetation of gigital signal processing systems
Applications and laboratory with MATLAB
Suggested readings (Search our library's catalogue)
Textbook
F.Argenti,L.Mucchi,E. Del Re, "Elaborazione numerica dei segnali. Teoria, esercizi ed esempi al calcolatore", McGraw-Hill, Milano, 2011.
Other textbooks
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
F.Argenti,L.Mucchi,E. Del Re, "Elaborazione numerica dei segnali. Teoria, esercizi ed esempi al calcolatore", McGraw-Hill, Milano, 2011.
Other textbooks
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
Learning Objectives
Learned knowledge:
Knowledge of advantages and limits of basic digital signal processing techniques.
Analysis and design of digital filters and FFT.
Basic digital signal processing components (including A/D and D/A and DSP).
Typical applications of digital signal processing.
Knowledge of advantages and limits of basic digital signal processing techniques.
Analysis and design of digital filters and FFT.
Basic digital signal processing components (including A/D and D/A and DSP).
Typical applications of digital signal processing.
Prerequisites
Signal theory
Teaching Methods
Classroom lectures
Exercises
Laboratory examples
Exercises
Laboratory examples
Further information
More information and additional didactic material from MOODLE e-learning platform available at the link:
http://e-l.unifi.it/
http://e-l.unifi.it/
Type of Assessment
Written exam.
At student choice: Optional oral exam at the same session of the written exam (usually two days later).
The student can submit a MATLAB exercise 15 days before the written exam, which will be evaluated together with the written and/or oral exam.
At student choice: Optional oral exam at the same session of the written exam (usually two days later).
The student can submit a MATLAB exercise 15 days before the written exam, which will be evaluated together with the written and/or oral exam.
Course program
Detailed program
Digital representation of signals
Signal sampling: ideal, base band signals, band pass signals, I and Q components, random signals. Real sampling, spectral distortion. Reconstruction of digital signals: digital-to-analog conversion.
Quantization. Signal to quantization error power ratio.
Analysis of discrete linear time-invariant systems.
Discrete systems: linearity, time-invariance, causality, stability. Linear-phase and minimum-phase systems. Energy and power. Z transform. Fourier transform.
Impulse response. Finite-difference equations.
Transfer function. Frequency response: amplitude and phase.
Filtering of random signals.
Equivalence of digital and analog filtering.
Discrete Fourier transform (DFT)
Properties. Relations with Fourier transform and Z transform.
Fast algorithms: Fast Fourier transform (FFT). Radix-2 algorithms: decimation-in-time and decimation-in-frequency. Other algorithms: radix-4 and mixed-radix.
Applications of DFT: spectral estimation, linear convolution and correlation.
Design of finite-impulse-response digital filters (FIR)
Properties of FIR filters. Linear-phase filters. "Half-band' filters.
Design methods: window, frequency sampling, Chebychev criterion. Design formulas. Examples: generalized band-pass, differentiator, Hilbert transformer. Generation of discrete analytic signal.
Design of infinite-impulse-response digital filters (IIR)
Properties, Stability. First and second order sections. All-pass. Minimum-phase IIR filters..
Design methods: from analog prototypes, direct design..
Comparison of FIR and IIR filters.
Implementation of digital signal processing systems.
Characteristics of digital signal processing algorithms and systems. .
Implementation complexity: evaluation parameters.
Discrete components: multiplier, multiplier-and accumulator, auxiliary circuits. Digital Signal Processor (DSP). Distibuted-arithmetic implementation.
Digital representation of signals
Signal sampling: ideal, base band signals, band pass signals, I and Q components, random signals. Real sampling, spectral distortion. Reconstruction of digital signals: digital-to-analog conversion.
Quantization. Signal to quantization error power ratio.
Analysis of discrete linear time-invariant systems.
Discrete systems: linearity, time-invariance, causality, stability. Linear-phase and minimum-phase systems. Energy and power. Z transform. Fourier transform.
Impulse response. Finite-difference equations.
Transfer function. Frequency response: amplitude and phase.
Filtering of random signals.
Equivalence of digital and analog filtering.
Discrete Fourier transform (DFT)
Properties. Relations with Fourier transform and Z transform.
Fast algorithms: Fast Fourier transform (FFT). Radix-2 algorithms: decimation-in-time and decimation-in-frequency. Other algorithms: radix-4 and mixed-radix.
Applications of DFT: spectral estimation, linear convolution and correlation.
Design of finite-impulse-response digital filters (FIR)
Properties of FIR filters. Linear-phase filters. "Half-band' filters.
Design methods: window, frequency sampling, Chebychev criterion. Design formulas. Examples: generalized band-pass, differentiator, Hilbert transformer. Generation of discrete analytic signal.
Design of infinite-impulse-response digital filters (IIR)
Properties, Stability. First and second order sections. All-pass. Minimum-phase IIR filters..
Design methods: from analog prototypes, direct design..
Comparison of FIR and IIR filters.
Implementation of digital signal processing systems.
Characteristics of digital signal processing algorithms and systems. .
Implementation complexity: evaluation parameters.
Discrete components: multiplier, multiplier-and accumulator, auxiliary circuits. Digital Signal Processor (DSP). Distibuted-arithmetic implementation.