Signal Processing-Sensors-Applications (NDT)

COURSE CONTENT

Introduction to digital signal processing, basic theory, signals and systems approach, Linear shift invariant (LSI) systems properties, frequency response of LSI systems, Discrete Time Fourier Transform, z-transform, Discrete Fourier Transform, FFT, Power spectrum and averaging, periodogram and Welch transform, Filters, Introduction to time-frequency transforms, Short time FFT, Wigner-Ville, Introduction to Wavelet transform, applications in Matlab.

LEARNING OUTCOMES

The goal of the module is to acquaint the student with the fundamental signal processing techniques and to apply them in an engineering project that runs throughout the semester. Basic digital signal processing techniques such as Discrete Fourier Transform as well as state-of-the-art ones (Wigner-Ville, wavelet transform etc) are presented and thoroughly discussed. Emphasis is given on the mathematical descriptions as well as to their practical implementation with Matlab.