The course aims at providing students with a basic knowledge and practice about the use of computer algorithms to perform image processing on digital images. The two main objectives attached to Digital Image Processing (DIP) are to improve the visual quality of images and to automatically extract semantic information from visual data (e.g. object recognition).
Teaching and Learning Methods: Each session is split into two parts: 1.5-hour lecture and 1.5-hour lab.
Course Policies: It is mandatory to attend lab. sessions.
Programming Languages and Algorithm Design has the following objectives:
- Introduce students to basic programming concepts and programming tools;
- Study three programming languages: C, as an example of low-level language; Python, as an example of high-level language; and MATLAB, as an example of domain-specific language;
- Provide students with methods and knowledge suitable for the design of efficient algorithms;
- Provide methods for the analysis of resources (memory and time) used by algorithms;
- Provide a catalogue of the most well-known and efficient algorithms for basic computational problems (sorting, searching, resource optimization, etc.).
Teachind and Learning methods:
The course is composed by lectures and laboratory sessions. The laboratory sessions consist in interactive crash courses (2 sessions of 3 hours each for each programming language, see “Course Structure” below) where the students have the opportunity of learning the basic programming concepts of different programming languages.
Course policies:
The course is composed by lectures, laboratory sessions in the form of interactive crash courses, and a mini student project.
Interactive:
The laboratory sessions will be interactive and will include discussions with the students and lab exercises. It will be held in one lab room equipped with a projector.
Crash curse:
The course will be structured into two sessions of 3 hours each.
The first session will serve as introduction to the programming language and corresponding programming tools. After a short description of the purpose and characteristics of the environment and programming language, the students will be guided through lab exercises to familiarize with the software and the basic programming concepts.
The second session will introduce additional libraries with a particular emphasis on the ones used in EURECOM courses.
The discussion will be alternated with lab exercises. The students will be given some time to solve a problem and then a volunteer student will be asked to show their solution to the other students using the computer connected to the projector.
The objective is to ensure that all students participate in the discussions and present their solution at least once during the course.
This class approaches wireless communication from the perspective of digital signal processing (DSP). No background in digital communication is assumed, though it would be helpful. The utility of a DSP approach is due to the following fact: wireless systems are bandlimited. This means that with a high enough sampling rate, thanks to Nyquist’s theorem, we can represent the bandlimited continuous-time wireless channel from its samples. This allows us to treat the transmitted signal as a discrete-time sequence, the channel as a discrete-time linear time invariant system, and the received signal as a discrete-time sequence. In this class, we take an experimental approach to wireless digital communication. We will use a well-known software defined radio platform known as the USRP (universal software radio peripheral) where the radio can be programmed in software instead of implemented using hardware. The focus will be on the design, implementation, evaluation, and iterative optimization of a digital wireless communication link. At the end of this class, you will have constructed your own wireless communication link. In this process, you will have achieved the following learning objectives. You will understand what bandlimited system is and how sampling works. You will be able to compute power spectra of bandlimited signals. You should be able to describe the design challenges associated with building a wireless digital communication link. You should be able to define and calculate bit error rates for some common modulation schemes. You should know the difference between binary phase shift keying and quadrature phase shift keying as well as how to implement them. You should understand the connection between pulse shaping and sampling. You should know how to define excess bandwidth for a raised-cosine pulse. You should understand how to obtain a sampled channel impulse response from a continuous time propagation channel. You should understand how to train and estimate the coefficients of a frequency selective channel. You should understand the various kinds of synchronization required and how to compensate for different sources of asynchronicity. You should be able to explain how to perform equalization using single carrier frequency domain equalization or OFDM modulation.
Teaching and Learning methods: /
Course Policies:/
The aim of this course is to introduce students to physical and psycho acoustics, digital audio technologies, sound processing and synthesis techniques specific to live-sound, audio and music applications. Special emphasis is placed on practice with the support of audio-specific software.
Teaching and Learning Methods: The lecture is divided in half between the theoretical part, which is enriched by sound examples, and practice in the laboratory.
Course Policies: Attendance to lectures and labs is not mandatory but highly recommended.
Description
The course will cover:
- Physical and psycho acoustics;
- Fundamentals of digital audio;
- Techniques and technologies for sound analysis, processing and synthesis;
- Hands-on practice with dedicated audio deployment tools.
The detailed course programme can be viewed at this link: https://www.massimilianotodisco.eu/teaching.html
Learning outcome
Students will be able to:
- understand and identify the fundamental characteristics of sound for the physical and perceptual world;
- understand the principles of digital audio;
- select and implement established signal processing and synthesis methods for sound and music signals;
- develop and evaluate practical sound-based applications.
Bibliography
- Fletcher, N. H., & Rossing, T. D. (1991). The physics of musical instruments. New York, Springer-Verlag.
- Vaseghi, S. V. (2007). Multimedia Signal Processing: Theory and Applications in Speech, Music and Communications. J. Wiley.
- Everest, F. and Pohlmann, K. (2001). Master Handbook of Acoustics. 5th ed. New York, McGraw-Hill.
- Müller, M. (2015). Fundamentals of Music Processing - Audio, Analysis, Algorithms, Applications. Springer.
- Course slides.
Requirements: Proficiency in mathematics, physics and statistics.
Grading Policy: Exam (80%) + Lab test (20%)
Nb hours of lectures/labs: 10.5/10.5
Nb hours per week: 3
Hot Topics in Mobile Communications
· This course presents some recent or emerging HOT TOPICS within the area of mobile networks.
· The course is modified from 2014 (and earlier) versions to allow focus on updated set of hot topics and trends in mobile communications.
· We emphasize emerging techniques to be used in future 5G mobile networks to allow for a significant increase in user quality, and network capacity.
· The course earns 5 ECTS
· We cover hot topics for 5G such as "Massive MIMO" , "network cooperation", "interference management", and "device coordination". These topics cover 21 hours.
· In the other 21hours, external experts (Intel, Huawei, ETSI, etc.) from Industry reveal hot topics seen from the wireless networking industry.
Teaching and Learning Methods : Lectures, Exercise and Lab sessions (group of 2 students)
Course Policies : Attendance to Lab session is mandatory (25% of final grade).
Digital communications is the study of physical layer transmission and reception strategies in communications equipment such as mobile communication devices, high-speed ethernet, optical communications and subscriber-line communications. It comprises the areas of (i) statistical modelling of communication channels (ii) design of coding and modulation systems for error resiliency (iii) design of demodulation and decoding strategies and the associated methods for assessing their performance. In addition to providing an overview of communication channels and classical modulation strategies, this course takes a hands-on approach by focusing on the details of a few critical elements of digital communications pertaining to modern wireless transceivers, both coherent and non-coherent.
Teaching and Learning Methods :: Lectures and hands-on lab sessions in MATLAB using signals acquired from local 4G networks.
Course Policies : Attendance to lab sessions is mandatory.
This course aims to present a treatment of mathematical methods suitable for engineering students who are interested in the rapidly advancing areas of signal analysis, processing, filtering and estimation. Significant current applications relate to, e.g., speech and audio, music, wired and wireless communications, instrumentation, multimedia, radar, sonar, control, biomedicine, transport and navigation. The course presents a study of linear algebra, probability, random variables, and analogue systems as a pre-requisite to material relating to sampled-data systems. Time permitting, the final part of the course covers the concepts of random processes, the analysis of random signals, correlation and spectral density.
Teaching and Learning Methods: The course is comprised of lectures, exercises and laboratory sessions.
Course policies: This course is aimed at students who have NOT already completed preparatory classes. Completion of all in-lecture examples is strongly advised.
The goal of MOBCOM is to provide a fundamental understanding of mobile communication systems. The course will seek to describe the key aspects of channel characteristics/modeling, of communication techniques, and to describe the application of these techniques in wireless communication systems.
Teaching and Learning Methods : Lectures and Lab sessions (group of 2-3 students)
Course Policies : Attendance to Lab session is mandatory.
This course presents a series of mobile systems in their entirety to synthetize the knowledge gained in more fundamental courses. It explores current and emerging standards and follows the evolution of various mobile services.
Teaching and Learning Methods : Lectures and Lab sessions (group of 2 students)
Course Policies : Attendance to Lab session is mandatory.
Would you like to investigate beyond the surface of Windows, MacOS, Linux, Android? Fed up with not understanding the origin of segmentation faults, why you need to eject a USB key before physically removing it, or why/how your Android system can execute Pokemon Go and Facebook at the same time? You want to delve into the details of the inner workings of the Linux kernel? Join us to discover the power of Operating Systems!
Teaching and Learning Methods : Lectures (40%), Lab sessions (40%), Project (20%)
Course Policies: Attendance to some lab and project session is mandatory
This course covers a variety of topics, all related to the use and management of a Linux operating system. In particular, the course is divided in three parts dedicated respectively to the command-line, to the Python programming language, and to maintaining, compiling, and installing applications.
« Those who fail to plan, plan to fail... ». Architects, tailors, and directors all use plans (or models) for their creation, and software engineers are no exception. Thus, it is a common practice for software project managers to rely on the UML langage to document their software projects, and to perform modeling of the software itself.
Teaching and Learning Methods : Lectures (20%), Exercises (40%), Lab sessions (40%)
Course Policies: Attendance to labs is mandatory
The proper treatment of modern communication systems requires the modelling of signals as random processes. Often the signal description will involve a number of parameters such as carrier frequency, timing, channel impulse response, noise variance, interference spectrum. The values of these parameters are unknown and need to be estimated for the receiver to be able to proceed.
Parameters may also occur in the description of other random analysis of communication networks, or in the descriptions of sounds and images, or other data, e.g. geolocation. This course provides an introduction to the basic techniques for estimation of a finite set of parameters, of a signal spectrum or of one complete signal on the basis of a correlated signal (optimal filtering, Wiener and Kalman filtering). The techniques introduced in this course have a proven track record of many decades. They are complementary to the techniques introduced in the EURECOM course Stat. They are useful for other application branches such as machine learning, in the EURECOM courses MALIS and ASI.
Teaching and Learning Methods: Lectures, Homework, Exercise and Lab session (groups of 1-2 students depending on size of class).
Course Policies: Attendance of Lab session is mandatory (15% of final grade).
This course provides a broad introduction to cryptography and communication security mechanisms based on cryptography. The course covers fundamental aspects such as security evaluation criteria and the mathematical constructs underlying cryptographic primitives as well as applied aspects like the design of major encryption and hashing algorithms, details of security mechanisms relying on cryptography such as data encryption, integrity, digital signature, authentication, key management, and public-key infrastructures.
Teaching and Learning Methods : Lectures and Lab sessions
Course Policies : Attendance to Lab sessions is mandatory.
Teaching and Learning methods: Weekly lectures and Laboratories