Displaying 83 resources
Laplace Transform
This lecture presents Laplace Transform (LT) and its region of convergence. Its relation to Laplace transform is presented. Notable LT properties are reviewed: time shift, convolution, signal differentiation/integration.
Z Transform
This lecture overviews Z Transform that has many applications in signal processing and systems theory.
Attention and Transformers Networks
In this lecture, the limitations of Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs) in effectively processing sequences are emphasized.
Artificial Neural Networks. Perceptron
This lecture will cover the basic concepts of Artificial Neural Networks (ANNs): Biological neural models, Perceptron, Activation functions, Loss types, Steepest Gradient Descent, On-line Perceptron training, Batch Perceptron training.
Statistical Detection
This lecture overviews Statistical Detection that has many applications in Machine Learning, Signal Analysis and Statistical Communications.
Introduction to Signals and Systems
This lecture overviews Signals and Systems. 1D signals, 2D signals (images), 3D signals (videos, medical volumes) are presented. Multichannel signals come next.