Fabio POSTIGLIONE | Signal Theory
Fabio POSTIGLIONE Signal Theory
cod. 0612700010
SIGNAL THEORY
| 0612700010 | |
| DIPARTIMENTO DI INGEGNERIA DELL'INFORMAZIONE ED ELETTRICA E MATEMATICA APPLICATA | |
| EQF6 | |
| COMPUTER ENGINEERING | |
| 2019/2020 |
| OBBLIGATORIO | |
| YEAR OF COURSE 2 | |
| YEAR OF DIDACTIC SYSTEM 2017 | |
| SECONDO SEMESTRE |
| SSD | CFU | HOURS | ACTIVITY | ||
|---|---|---|---|---|---|
| ANALISI DEI SEGNALI (Modulo di TEORIA DEI SEGNALI) | |||||
| ING-INF/03 | 4 | 32 | LESSONS | ||
| ING-INF/03 | 2 | 16 | EXERCISES | ||
| ELEMENTI DI PROBABILITÀ (Modulo di TEORIA DEI SEGNALI) | |||||
| SECS-S/02 | 4 | 32 | LESSONS | ||
| SECS-S/02 | 2 | 16 | EXERCISES | ||
| Objectives | |
|---|---|
| THE COURSE IS METHODOLOGICAL AND AIMS AT PROVIDING THE TOOLS AND FUNDAMENTAL METHODS FOR DESCRIBING AND EXAMINING NON-DETERMINISTIC PHENOMENA, AND AT INTRODUCING THE BASIC TECHNIQUES FOR SIGNAL ANALYSIS AND PROCESSING, WITH EMPHASIS ON THE TIME-FREQUENCY DUALITY. THE PRESENTED TOOLS AND METHODS HAVE WIDESPREAD APPLICATION IN COMPUTER SCIENCE, ELECTRONICS AND TELECOMMUNICATIONS. THE COURSE CONTENTS ARE PREPARATORY FOR THE SUBSEQUENT COURSES OF THE TELECOMMUNICATIONS AREA. KNOWLEDGE AND UNDERSTANDING UNDERSTANDING THE BASIC TERMINOLOGY USED IN PROBABILITY THEORY. RANDOM VARIABLES MODELS AND RELATED TRANSFORMATIONS. NOTIONS OF STOCHASTIC PROCESSES. COMBINATORIAL CALCULUS. SIGNAL PROCESSING TECHNIQUES IN THE TIME AND FREQUENCY DOMAINS, FOR CONTINUOUS AS WELL AS FOR DISCRETE TIME SIGNALS. UNDERSTANDING THE EFFECT OF SYSTEMS ON BOTH ANALOG AND DIGITAL SIGNAL PROCESSING. DIGITAL-TO-ANALOG CONVERSION. DISCRETE FOURIER TRANSFORM. APPLIED KNOWLEDGE AND UNDERSTANDING ABILITY TO MODEL AND ANALYZE RANDOM EVENTS, IN CONNECTION TO REAL-WORLD PHENOMENA. ABILITY TO CHARACTERIZE SYSTEMS IN TERMS OF INPUT/OUTPUT RELATIONSHIPS, ESPECIALLY AS REGARDS LTI SYSTEMS. ABILITY TO DESIGN AND PERFORM SIMPLE SIGNAL PROCESSING TECHNIQUES, IN CONNECTION TO SIGNALS OF PRACTICAL INTEREST. ABILITY TO APPLY THE BASIC CONCEPTS OF ANALOG/DIGITAL SIGNAL CONVERSION. |
| Prerequisites | |
|---|---|
| PREREQUISITES: SUITABLE KNOWLEDGE OF MATHEMATICS. BASICS OF SET THEORY. PREPARATORY COURSES: MATHEMATICAL ANALYSIS 2. |
| Contents | |
|---|---|
| - ELEMENTS OF PROBABILITY THEORY. ELEMENTS OF PROBABILITY THEORY AND COMBINATORIAL CALCULUS. AXIOMS OF PROBABILITY. CONDITIONAL PROBABILITY AND INDEPENDENCE. TOTAL PROBABILITY THEOREM. BAYES THEOREM. COMBINATORIAL CALCULUS. (HOURS: LESSONS/EXERCISES/LABORATORY 6/4/0) RANDOM VARIABLES AND PROBABILISTIC MODELS OF COMMON USE. DEFINITION OF A RANDOM VARIABLE (R.V.). CONTINUOUS AND DISCRETE RANDOM VARIABLES. PROBABILITY DISTRIBUTION. PROBABILITY DENSITY FUNCTION AND PROBABILITY MASS FUNCTION. SUMMARY DESCRIPTORS (MEAN, VARIANCE, MEDIAN,...). FUNCTIONS OF A RANDOM VARIABLE. PAIRS OF R.V.S. JOINT AND MARGINAL DISTRIBUTIONS. SUMMARY DESCRIPTORS FOR PAIRS OF RANDOM VARIABLES. (HOURS: LESSONS/EXERCISES/LABORATORY 10/6/0) BASIC LAWS OF PROBABILITY THEORY. TRANSFORMATIONS OF RANDOM VARIABLES. SUM OF INDEPENDENT R.V.S. LAW OF LARGE NUMBERS AND THE CENTRAL LIMIT THEOREM. (HOURS: LESSONS/EXERCISES/LABORATORY 13/5/0) INTRODUCTION TO STOCHASTIC PROCESSES. DEFINITION OF A STOCHASTIC PROCESS AND ITS PROPERTIES: STATIONARITY, WEAK-SENSE STATIONARITY, AND ERGODICITY. GAUSSIAN PROCESSES. (HOURS: LESSONS/EXERCISES/LABORATORY 13/5/0) - SIGNAL ANALYSIS. SIGNALS AND SYSTEMS IN THE TIME DOMAIN. CLASSIFICATION AND BASIC OPERATIONS OF DISCRETE-TIME AND CONTINUOUS-TIME SIGNALS. TIME AVERAGES, ENERGY AND POWER OF DETERMINISTIC SIGNALS. PERIODIC SIGNALS. CORRELATION FUNCTION AND ITS PROPERTY. SYSTEM ANALYSIS IN TIME DOMAIN. SYSTEM PROPERTIES AND LINEAR TIME-INVARIANT (LTI) SYSTEMS. CONVOLUTION INTEGRAL AND SUM. (HOURS: LESSONS/EXERCISES/LABORATORY 16/8/0) SIGNALS AND SYSTEMS IN THE FREQUENCY DOMAIN. FREQUENCY-DOMAIN REPRESENTATION OF SYSTEMS AND SIGNALS: FOURIER TRANSFORM AND ITS PROPERTIES. POISSON SUM AND FOURIER SERIES. FREQUENCY-DOMAIN LTI SYSTEM ANALYSIS. ENERGY AND POWER SPECTRA OF SIGNALS. INPUT-OUTPUT RELATIONSHIP FOR ENERGY AND POWER SPECTRA AND CORRELATION FUNCTIONS. (HOURS: LESSONS/EXERCISES/LABORATORY 8/4/0) DIGITAL SIGNAL PROCESSING. RELATIONSHIP BETWEEN SAMPLING OPERATION AND REPLICATION OF SIGNALS INTRODUCED BY FOURIER TRANSFORM. NYQUIST-SHANNON SAMPLING THEOREM AND ITS PRACTICAL IMPLEMENTATIONS: ANTI-ALIASING FILTER, SAMPLE & HOLD SAMPLING PROCEDURE. DIGITAL PROCESSING OF ANALOG SIGNALS. ANALOG-TO-DIGITAL CONVERSION. DISCRETE FOURIER TRANSFORM (DFT). (HOURS: LESSONS/EXERCISES/LABORATORY 7/5/0) |
| Teaching Methods | |
|---|---|
| THE COURSE INCLUDES THEORETICAL LECTURES AND CLASSROOM EXERCISES. SOME CLASSROOM EXERCISES CAN BE SOLVED BY USING MATLAB DURING THE LABORATORY ACTIVITY. IN ORDER TO PARTICIPATE TO THE FINAL ASSESSMENT AND TO GAIN THE CREDITS CORRESPONDING TO THE COURSE, THE STUDENT MUST HAVE ATTENDED AT LEAST 70% OF THE HOURS OF ASSISTED TEACHING ACTIVITIES. |
| Verification of learning | |
|---|---|
| THE FINAL EXAM IS ONE AND THE SAME FOR BOTH UNITS. ITS GOAL IS THE EVALUATION OF THE KNOWLEDGE AND UNDERSTANDING OF THE CONCEPTS PRESENTED DURING THE COURSE, THE ABILITY TO APPLY THAT KNOWLEDGE TO SOLVE PROBLEMS ON PROBABILITY, ON THE ANALYSIS OF SIGNALS AND SYSTEMS BOTH IN TIME AND FREQUENCY DOMAINS, ON THE SAMPLING OF TIME-CONTINUOUS SIGNALS. FURTHERMORE, THE PERSONAL JUDGEMENT, THE COMMUNICATION SKILLS AND THE LEARNING ABILITIES ARE ALSO EVALUATED. THE FINAL EXAM CONSISTS OF A WRITTEN TEST AND AN ORAL INTERVIEW: A)THE WRITTEN TEST AIMS TO ASSESS THE ABILITY TO SOLVE PROBLEMS ABOUT THE TOPICS PRESENTED DURING THE COURSE, SUCH AS: 1) PROBABILITY AND COMBINATORIAL CALCULUS; 2) ANALYSIS OF SIGNALS AND SYSTEMS BOTH IN TIME AND FREQUENCY DOMAINS; 3) SAMPLING OF TIME-CONTINUOUS SIGNALS. THE WRITTEN TEST IS EVALUATED ON THE BASIS OF THE CORRECTNESS OF THE APPROACH AND RESULTS ACCORDING TO THE FOLLOWING SCALE: “EXCELLENT” (A), “GOOD” (B), “FAIR” (C), “SUFFICIENT” (D), “BARELY SUFFICIENT” (E), “INSUFFICIENT” (F). THE “INSUFFICIENT” (F) SCORE IMPLIES THE WRITTEN TEST REPETITION. THE “BARELY SUFFICIENT” (E) SCORE CORRESPONDS TO A LAME WRITTEN TEST AND IMPLIES THAT THE STUDENT SHOULD MAKE UP THE PROBLEMS OF HIS/HER TEST DURING THE ORAL INTERVIEW. B)THE ORAL INTERVIEW AIMS TO VERIFY THE ACQUIRED KNOWLEDGE ALSO ON THE TOPICS NOT COVERED BY THE WRITTEN TEST. THE ORAL EXPOSITION AND THE MATHEMATICAL ARGUMENTS ARE CREDITED WITH HIGHER SCORES. AN ORAL INTERVIEW THAT IS NOT CONSIDERED SUFFICIENT IMPLIES THE REPETITION OF THE WRITTEN TEST, TOO. |
| Texts | |
|---|---|
| ELEMENTS OF PROBABILITY THEORY: A. PAPOULIS, S. U. PILLAI, PROBABILITY, RANDOM VARIABLES AND STOCHASTIC PROCESSES, 4TH ED., MCGRAW-HILL, 2001. S. M. ROSS, PROBABILITÀ E STATISTICA PER L’INGEGNERIA E LE SCIENZE, APOGEO, 2008. SIGNAL ANALYSIS: E. CONTE, LEZIONI DI TEORIA DEI SEGNALI, LIGUORI,1996 M. LUISE, G. M. VITETTA, TEORIA DEI SEGNALI, 3RD ED., MCGRAW-HILL, 2009. V. OPPENHEIM, A. S. WILLSKY, S. HAMID NAWAB, SIGNALS & SYSTEMS, 2ND ED., PRENTICE-HALL, 1997. V. K. INGLE, J. G. PROAKIS, DIGITAL SIGNAL PROCESSING USING MATLAB, 3RD ED., CENGAGE LEARNING, 2011. |
| More Information | |
|---|---|
| THE COURSE LANGUAGE IS ITALIAN. |
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