The student should have basic knowledge of - probability theory and statistics - linear algebra.

The main objective of this course is that the student acquires the basic knowledge/tools to be able to complete Statistical Signal Processing

Probability theory: introduction, random variables, probability distribution and density functions, mathematical expectation and moments. Stochastic processes: introduction, first- and second-order statistics, stationarity and power spectral density Linear algebra: introduction, matrix algebra and matrix decompositions

LEARNING ACTIVITIES AF3 Theoretical practical classes AF4 Laboratory practices AF5 Tutorials AF6 Team work AF7 Student individual work AF8 Partial and final exams METHODOLOGY MD1: Class lectures by the professor with the support of computer and audiovisual media, in which the main concepts of the course are developed and complemented with bibliography. MD2: Critical reading of texts recommended by the professor of the course. MD3: Resolution of practical cases, problems, etc. .... posed by the teacher individually or in groups. MD4: Presentation and discussion in class, under the moderation of the professor, of topics related to the content of the course, as well as case studies. MD5: Elaboration of works and reports individually or in groups. CONSULTATION HOURS The students will be able to consult with the instructor during 2 or 3 hours per week