Stefano MARANO | SIGNAL ANALYSIS
Stefano MARANO SIGNAL ANALYSIS
cod. 0612700136
SIGNAL ANALYSIS
| 0612700136 | |
| DIPARTIMENTO DI INGEGNERIA DELL'INFORMAZIONE ED ELETTRICA E MATEMATICA APPLICATA | |
| EQF6 | |
| COMPUTER ENGINEERING | |
| 2022/2023 |
| OBBLIGATORIO | |
| YEAR OF COURSE 2 | |
| YEAR OF DIDACTIC SYSTEM 2017 | |
| AUTUMN SEMESTER |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| ING-INF/03 | 3 | 24 | LESSONS | |
| ING-INF/03 | 3 | 24 | EXERCISES | |
| ING-INF/03 | 3 | 24 | LAB |
| Objectives | |
|---|---|
| THE COURSE PROVIDES THE BASIC TOOLS AND METHODS FOR MODELING AND ANALYZING SIGNALS, IN TIME AND FREQUENCY DOMAINS, AND THE FUNDAMENTALS OF SIGNAL TRANSMISSION. KNOWLEDGE AND UNDERSTANDING: PROBABILITY AND RANDOM VARIABLES. REPRESENTATION OF PERIODIC SIGNALS. SIGNAL SPACE. CONTINUOUS AND DISCRETE FOURIER TRANSFORMS. ANALYSIS OF SIGNAL AND SYSTEMS IN CONTINUOUS AND DISCRETE TIME, DETERMINISTIC AND RANDOM, IN TIME AND FREQUENCY DOMAINS. A/D CONVERSION AND DIGITAL SIGNAL PROCESSING. DIGITAL TRANSMISSIONS. APPLIED KNOWLEDGE AND UNDERSTANDING APPLYING PROBABILITY AND STATISTICAL TOOLS TO SOLVE SIGNAL PROCESSING TASKS AND COMMUNICATION PROBLEMS (E.G., DETECTION AND CLASSIFICATION OF SIGNALS TRANSMITTED OVER NOISY CHANNELS). DESIGN OF THE MAIN BLOCKS FOR ANALOG TO DIGITAL CONVERSION. DESIGN OF SIMPLE DIGITAL MODULATION SCHEMES. PERFORMANCE ANALISYS (ERROR PROBABILITY) OF DIGITAL COMMUNICATIONS SCHEMES VERSUS BANDWIDTH AND POWER. |
| Prerequisites | |
|---|---|
| PREREQUISITES: SUITABLE KNOWLEDGE OF MATHEMATICS. PREPARATORY COURSES: MATHEMATICAL ANALYSIS II. |
| Contents | |
|---|---|
| TOTAL LECTURE/PRACTICE/LABORATORY (LEC/PRA/LAB) HOURS: 48/24/0 1 (2H LEC): INTRODUCTION TO THE COURSE LEARNING UNIT (LU) 1: BASIC ELEMENTS OF PROBABILITY (LECT/PRA/LAB: 12/4/0) 2 (2H LEC): AXIOMS AND THEIR IMPLICATIONS 3 (2H LEC): CONDITIONAL PROBABILITY AND INDEPENDENCE. TOTAL PROBABILITY THEOREM. BAYES THEOREM. 4 (2H PRA): EXERCISES ON BASIC PROBABILITY AND INDEPENDENCE 5 (2H LEC): RANDOM VARIABLES AND STANDARD PROBABILISTIC MODELS. CONTINUOUS AND DISCRETE RANDOM VARIABLES 6 (2H LEC): DISTRIBUTIONS, PROBABILITY DENSITY AND PROBABILITY MASS FUNCTION 7 (2H LEC): MOMENTS OF RANDOM VARIABLES (MEAN, VARIANCE, COVARIANCE) 8 (2H LEC): JOINT AND MARGINAL DISTRIBUTIONS 9 (2H PRA): EXERCISES ON RANDOM VARIABLES KNOWLEDGE AND UNDERSTANDING SKILLS. UNDERSTANDING BASIC ELEMENTS FOR PROBABILITY CALCULUS AND MANIPULATION OF RANDOM VARIABLES APPLIED KNOWLEDGE AND UNDERSTANDING SKILLS. APPLY BASIC TECHNIQUES TO SOLVE PROBABILITY, DECISION, CLASSIFICATION, AND ESTIMATION PROBLEMS LU2: SIGNAL AND SYSTEMS (LECT/PRA/LAB: 22/10/0) 10 (2H LEC): SIGNAL SPACES. ELEMENTARY OPERATIONS AND PROPERTIES OF SIGNALS 11 (2H LEC): ELEMENTARY SIGNALS. PERIODIC SIGNALS 12 (2H LEC): TIME AVERAGES. ENERGY AND POWER 13 (2H PRA): EXERCISES ON SIGNALS IN THE TIME DOMAIN, ENERGY AND POWER 14 (2H LEC): PROPERTIES OF SYSTEMS 15 (2H LEC): LTI SYSTEMS. CONVOLUTION SUM AND INTEGRAL 16 (2H PRA): EXERCISES ON SYSTEM PROPERTIES AND LTI FILTERING IN TIME DOMAIN 17 (2H LEC): SIGNALS IN THE FREQUENCY DOMAIN. FREQUENCY RESPONSE. FOURIER TRANSFORM 18 (2H LEC): PROPERTIES OF THE FOURIER TRANSFORM 19 (2H PRA): EXERCISES ON FOURIER TRANSFORM AND PROPERTIES 20 (2H LEC): REPLICATION AND SAMPLING 21 (2H LEC): SPECTRUM OF PERIODIC SIGNALS AND FOURIER SERIES 22 (2H PRA): EXERCISES ON PERIODIC SIGNALS 23 (2H LEC): FREQUENCY DOMAIN ANALYSIS OF LTI SYSTEM. ENERGY CHARACTERIZATION IN THE FREQUENCY DOMAIN. I/O RELATIONSHIP FOR ENERGY AND POWER SPECTRAL DENSITIES. 24 (2H LEC): PRINCIPLES OF DIGITAL SIGNAL PROCESSING. SAMPLING AND RECONSTRUCTION. SAMPLING THEOREM. 25 (2H PRA): EXERCISES ON SAMPLING KNOWLEDGE AND UNDERSTANDING SKILLS UNDERSTANDING SIGNAL ANALYSIS IN TIME AND FREQUENCY DOMAINS, AND SAMPLING PRINCIPLES APPLIED KNOWLEDGE AND UNDERSTANDING SKILLS ANALYZE SIGNALS IN TIME AND FREQUENCY DOMAINS. DESIGN SIMPLE FILTERING AND SAMPLING SYSTEMS LU3: DIGITAL COMMUNICATION SYSTEMS (LEC/PRA/LAB: 12/10/0) 26 (2H LEC): DIGITAL TRANSMISSION SYSTEMS. AWGN CHANNEL 27 (2H LEC): PROBABILISTIC MODEL OF SIGNAL AT THE RECEIVER. RANDOM SIGNALS AND RANDOM VECTORS. TRANSFORMATION OF RANDOM VECTORS. 28 (2H PRA): EXERCISES ON RANDOM SIGNALS AND VECTORS 29 (2H LEC): VECTOR REPRESENTATION AND GRAM-SCHMIDT PROCESS 30 (2H LEC): 1D, 2D AND ORTHOGONAL MODULATION SCHEMES. BIT AND SYMBOL ERROR PROBABILITY 31 (2H PRA): EXERCISES ON SIGNAL REPRESENTATION. GRAM-SCHMIDT PROCESS 32 (2H LEC): PERFORMANCE OF BINARY MODULATIONS 33 (2H PRA): EXERCISES ON PERFORMANCE EVALUATION OF BINARY MODULATIONS 34 (2H LEC): PERFORMANCE OF MODULATIONS SCHEMES AND UNION BOUND 35 (2H PRA): EXERCISES ON PERFORMANCE EVALUATION 36 (2H PRA): RECAP EXERCISES KNOWLEDGE AND UNDERSTANDING SKILLS UNDERSTANDING BASIC ELEMENTS OF A DIGITAL MODULATION SCHEME FOR THE AWGN CHANNEL APPLIED KNOWLEDGE AND UNDERSTANDING SKILLS DESIGN SIMPLE DIGITAL MODULATION SYSTEMS AND EVALUATE THEIR PERFORMANCE |
| Teaching Methods | |
|---|---|
| THE COURSE INCLUDES THEORETICAL LECTURES AND CLASSROOM EXERCISES. |
| Verification of learning | |
|---|---|
| THE GOAL OF THE FINAL EXAM IS THE EVALUATION OF THE KNOWLEDGE AND UNDERSTANDING OF THE CONCEPTS PRESENTED DURING THE COURSE. FURTHERMORE, THE PERSONAL JUDGEMENT, THE COMMUNICATION SKILLS AND THE LEARNING ABILITIES ARE ALSO EVALUATED. THE FINAL EXAM CONSISTS OF A WRITTEN TEST POSSIBLY FOLLOWED BY AN ORAL INTERVIEW. THE WRITTEN TEST IS EVALUATED ON THE BASIS OF THE ABILITY TO FORMALIZE THE PROBLEM, THE CORRECTNESS OF THE RESULTS, THE CLARITY OF THE PRESENTATION, THE DEPTH OF UNDERSTANDING. A POSITIVE EVALUATION IS NECESSARY TO HAVE ACCESS TO THE ORAL EXAMINATION. THE ORAL EXAMINATION IS AIMED TO REFINE THE EVALUATION. 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. IN LINE WITH DEPARTMENT DECISIONS, COURSE PARTICIPANTS CAN UNDERGO AN INTERMEDIATE TEST, THAT ENABLES TO PARTICIPATE TO A FINAL TEST WITHIN THE EXAM SESSION JUST AFTER THE END OF THE COURSE. |
| Texts | |
|---|---|
| A. PAPOULIS, S. U. PILLAI, PROBABILITY, RANDOM VARIABLES AND STOCHASTIC PROCESSES, 4TH ED., MCGRAW-HILL, 2001. E. CONTE, LEZIONI DI TEORIA DEI SEGNALI, LIGUORI,1996 J. G. PROAKIS, M. SALEHI, FUNDAMENTALS OF COMMUNICATION SYSTEMS, 2ND ED., PEARSON, 2014. SUPPLEMENTARY TEACHING MATERIAL WILL BE AVAILABLE ON THE UNIVERSITY E-LEARNING PLATFORM (HTTP://ELEARNING.UNISA.IT) ACCESSIBLE TO STUDENTS USING THEIR OWN UNIVERSITY CREDENTIALS. |
| More Information | |
|---|---|
| THE COURSE IS HELD IN ITALIAN |
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