Stochastic simulation and bayesian methods for signal processing University of Bordeaux
![university-logo](media/course/2017/10/partner_logo_bordeaux.png)
Course Overview
This course completes the basis of computer programming applied to thesimulation of stochastic processes.
Learning Achievement
Competence
Course prerequisites
Grading Philosophy
> Intermediate assessment (mark I out of 20, duration 1h30 to 2h40during the semester) and final exam (mark E out of 20, duration 3h inDecember)- final mark I/3+2E/3> Rules and protocol for failures/re-sits is clearly described: incase of failure, student have access to a second exam(mark S)- the final mark is then max(I/3+2S/3,S)
Course schedule
Course content includes: - Monte Carlo methods and stochastic optimization algorithms -bayesian statisticsThe course will apply problems in data analysis and signal and imageprocessing (denoising, deconvolution, classification, segmentation,clustering).
Course type
Lectures
Online Course Requirement
Instructor
Other information
Mode of delivery: Face-to-face teaching
Site for Inquiry
Please inquire about the courses at the address below.
Contact person: Philippe JamingPhilippe.jaming@math.u-bordeaux.frNicole Bergerotnicole.bergerot@u-bordeaux.fr