Lecture 1. Signals and mathematical models
Lecture 2 Digital representation of signals
Lecture 3 Signal discretization by sampling
Lecture 4 Element-wise quantization
Lecture 5 Principles of signal and image coding
Lecture 6 Signal transformations and their discrete representation. Digital filters
Lecture 7 Discrete representations of Fourier Transform
Lecture 8 Applications of DFT and SDFTs
Lecture 9 Principles of signal parameter estimation
Lecture 10 Signal reconstruction and enhancement: linear filters
Lecture 11Signal/image restoration: nonlinear filters
Lecture 12 Correlational averaging as a method for signal restoration
Lecture 13 Ultrasound image processing for quantitative analysis of fetal movement
Test signals and images for exercises
