• General


    EE 503 Statistical Signal Processing and Modeling 
    (Fall 2020– 2021)

    Short Description: 

    This course is the first course on statistical signal processing in the graduate curriculum of Department of Electrical and Electronics Engineering, Middle East Technical University (METU). Topics covered in this course are random vectors, random processes, stationary random processes, wide sense stationary processes and their processing with LTI systems with applications in optimal filtering, smoothing and prediction. A major goal is to introduce the concept of mean square error (MSE) optimal processing of random signals by LTI systems. 

    For the processing of the random signals, it is assumed that some statistical information about the signal of interest and distortion is known. By utilizing this information, MSE optimal LTI filters (Wiener filters) are designed. This forms the processing part of the course. The estimation of the statistical information to construct Wiener filters forms the modeling part of the course. In the modeling part, we examine AR, MA, ARMA models for random signals and give a brief discussion of Pade, Prony methods for the deterministic modeling. Among other topics of importance are decorrelating transforms (whitening), spectral factorization, Karhunen-Loeve transform 

    Instructor: Cagatay Candan

    youtube-playlist for all 47 EE 503 lecture videos:

  • Lecture 1

  • Lecture 2

  • Lecture 3

  • Lecture 4

  • Lecture 5

  • Lecture 6

  • Lecture 7

  • Lecture 8

  • Lecture 9

  • Lecture 10

  • Lecture 11

  • Lecture 12a

  • Lecture 12b

  • Lecture 13

  • Lecture 14

  • Lecture 15

  • Lecture 16

  • Lecture 17

  • Lecture 18

  • Lecture 19

  • Lecture 20

  • Lecture 21

  • Lecture 22

  • Lecture 23a

  • Lecture 23b

  • Lecture 24

  • Lecture 25

  • Lecture 26

  • Lecture 27

  • Lecture 28

  • Lecture 29

  • Lecture 30

  • Lecture 31

  • Lecture 32

  • Lecture 33

  • Lecture 34

  • Lecture 35a

  • Lecture 35b

  • Lecture 36a

  • Lecture 36b

  • Lecture 37

  • Lecture 38

  • Lecture 39

  • Lecture 40

  • Lecture 41

  • Lecture 42