


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



Deep Reinforcement Learning
This lecture overviews Deep Reinforcement Learning that has many applications in, e.g., Game playing agents, Self-driving vehicles, Robotics (Robot cleaners) and Stock exchange agents.



Continuous-time Signals and Systems
This lecture overviews continuous-time Signals and Systems topics. Continuous-time signals are presented: periodic signals, delta function, unit step signal, exponential signal, trigonometric signals, complex exponential signal.



Robust Statistics
This lecture overviews Robust Statistics that has many applications in Data Analytics and Digital Signal Processing and Analysis. It covers the following topics in detail: Outliers.



Discrete-time Signals and Systems
This lecture overviews discrete-time Signals and Systems topics. Discrete-time signals are presented: periodic signals, delta signal, unit step signal, exponential signal, trigonometric signals, complex exponential signal.



Z Transform
This lecture overviews Z Transform that has many applications in signal processing and systems theory.