Digital processing of non-stationary signals

The objective of this course is that students master advanced techniques for digital processing of non-stationary signals acquired from dynamical systems primarily within manufacturing, as well as to acquire theoretical knowledge and practical skills necessary for effective extraction of representative features from signal.

After successfully completing this course, the students should be capable to: - Effectively de-noise one-dimensional and two-dimensional signals (acquired or in real time within control systems); - Carry out Fourier, short-time Fourier, Hilbert-Huang and discrete wavelet transform; - Generate system for features extraction from one-dimensional and two-dimensional signals; - Recognize and implement signal processing technique of choice for concrete problem solving.

Classification of signals; Fourier transform; discrete Fourier transform; short time Fourier transform; finite impulse response (FIR) filters; synthesis of FIR filters; infinite impulse response (IIR) filters; continuous wavelet transform; discrete wavelet transform; families of wavelets and their characteristics; multi-resolution analysis; two-dimensional wavelet transform; Hilbert-Huang transform; two-dimensional signal processing; comparative analysis of techniques for digital processing of non-stationary signals

Implementation of studied techniques in solving the selected practical problems in digital processing of non-stationary signals, depending on PhD thesis subject.

none

General purpose programming languages for practical realization of digital signal processing Data acquisition system А2Logger Software for data acquisition Sensors (accelerometers, distance, dynamometers…) Development systems based on microcontrollers for practical realization in real-time Compilers

Total assigned hours: 65

New material: 30
Elaboration and examples (recapitulation): 20

Auditory exercises: 0
Laboratory exercises: 0
Calculation tasks: 0
Seminar paper: 0
Project: 0
Consultations: 0
Discussion/workshop: 0
Research study work: 0

Review and grading of calculation tasks: 0
Review and grading of lab reports: 0
Review and grading of seminar papers: 10
Review and grading of the project: 0
Test: 0
Test: 0
Final exam: 5

Activity during lectures: 0
Test/test: 0
Laboratory practice: 0
Calculation tasks: 0
Seminar paper: 50
Project: 0
Final exam: 50
Requirement for taking the exam (required number of points): 35

Jakovljević, Ž., Petrović, P., Contact states recognition in robotized assembly, University of Belgrade, Faculty of Mechanical Engineering, 2011, ISBN: 978-86-7083-750-8 (in Serbian); Daubechies, I., Ten Lectures on Wavelets, CBMS-NSF regional conference series in applied mathematics, 61, Society for Industrial and Applied Mathematics, Philadelphia, Pennsylvania, 1992.; Mallat, S., A wavelet tour of signal processing, Academic Press, San Diego, California, 1999; Huang, N., E., et al., The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis, Proceedings of Royal Society London, Vol. 454, pp 903-995, 1998; Popović, M., V., Digital Signal Processing, Nauka, Beograd, 1994. (in Serbian)