Concept
Transducteur fini
Cours associés (19)
EE-110: Logic systems (for MT)
Ce cours couvre les fondements des systèmes numériques. Sur la base d'algèbre Booléenne et de circuitscombinatoires et séquentiels incluant les machines d'états finis, les methodes d'analyse et de syn
COM-302: Principles of digital communications
This course is on the foundations of digital communication. The focus is on the transmission problem (rather than being on source coding).
MATH-502: Distribution and interpolation spaces
The goal of this course is to give an introduction to the theory of distributions and cover the fundamental results of Sobolev spaces including fractional spaces that appear in the interpolation theor
CS-251: Theory of computation
This course constitutes an introduction to theory of computation. It discusses the basic theoretical models of computing (finite automata, Turing machine), as well as, provides a solid and mathematica
CS-173: Fundamentals of digital systems
Welcome to the introductory course in digital design and computer architecture. In this course, we will embark on a journey into the world of digital systems, exploring the fundamental principles and
PHYS-702: Advanced Quantum Field Theory
The course builds on the course QFT1 and QFT2 and develops in parallel to the course on Gauge Theories and the SM.
MATH-410: Riemann surfaces
This course is an introduction to the theory of Riemann surfaces. Riemann surfaces naturally appear is mathematics in many different ways: as a result of analytic continuation, as quotients of complex
PHYS-641: Quantum Computing
After introducing the foundations of classical and quantum information theory, and quantum measurement, the course will address the theory and practice of digital quantum computing, covering fundament
MGT-484: Applied probability & stochastic processes
This course focuses on dynamic models of random phenomena, and in particular, the most popular classes of such models: Markov chains and Markov decision processes. We will also study applications in q
MATH-432: Probability theory
The course is based on Durrett's text book
Probability: Theory and Examples.
It takes the measure theory approach to probability theory, wherein expectations are simply abstract integrals.
It takes the measure theory approach to probability theory, wherein expectations are simply abstract integrals.