Topics of week 4 are covered in the course book by the following chapters:

9.1, 9.2, 9.3, 9.4, 9.5.2, (9.5.3), 6.1, 6.2

and the exercises:

9.3(0), X14(0), 9.1(+1), 9.4(+1), 9.5(0), X12(0), X13(0), 9.2(+1), X15(0), X16(0), 6.1(0), 6.2(0), 6.3(+1), X17(0), 6.6(0), X18(+1), X21(+1)

An mp4-video (10-20 minutes) with slides presents the topic, where the corresponding slides also are included as a separate pdf-file. A number of suitable exercises is listed.

The numbered exercises are found in the course book and the exercises X1, X2 … are found in additional exercises (exercises and solutions). Solutions of the course book exercises are found in the solutions manual. The exercises are marked with three levels: (-1) if you have forgotten some of the prior knowledge or need extra training, (0) to be computed by everyone, (+1) if you like challenges.

Spectral estimation - bias and data windowing: 9.3(0), X14(0), 9.1(+1), 9.4(+1)

Est_spect_bias.mp4 W4_est_spect_bias.pdf

Spectral estimation - variance reduction: 9.5(0), X12(0), X13(0), 9.2(+1)

Est_spect_var.mp4 W4_est_spect_var.pdf

Introduction to filters: X15(0), X16(0), 6.1(0), 6.2(0), 6.3(+1)

Intro_filters.mp4 W4_intro_filters.pdf

Random harmonic functions and discrete time filters: X17(0), 6.6(0), X18(+1)

Filters_disc_time.mp4 W4_filters_disc_time.pdf

Example of covariance calculation of integrals: X21(+1)

Ex_cov_integral.mp4 W4_ex_cov_integral.pdf