


Fourier Transform
This lecture overviews the topics of continuous-time periodic signals, signal frequencies and Fourier Transform (FT). Its relation to Laplace transform is presented.



Discrete Fourier Transform
This lecture overviews Discrete Fourier Transform that has many applications in digital signal processing and analysis and in power spectrum estimation.



Fast Fourier Transform
This lecture overviews Fast Fourier Transform that has many applications in digital signal processing and analysis and in power spectrum estimation.



State – Space Equations
This lecture overviews State –Space Equations that has many applications in digital filters, systems theory and deep learning.



Probability Theory
This lecture overviews Probability Theory that has many applications in a multitude of scientific and engineering disciplines, notably in Pattern Recognition and Machine Learning. It covers the following topics in detail:



Statistical Detection
This lecture overviews Statistical Detection that has many applications in Machine Learning, Signal Analysis and Statistical Communications.