Lectures related to Stateful Operations and Materialized Values

Explores linear estimation, Wiener filters, and optimal prediction in signal processing.

Explores image filtering techniques, including linear and nonlinear filters, for artifact removal and feature enhancement.

Discrete-Time Stochastic Processes: Wiener Filter

Explores the Wiener filter for discrete-time stochastic processes and its applications.

Linear Prediction and Estimation

Explores linear prediction, optimal filters, random signals, stationarity, autocorrelation, power spectral density, and Fourier transform in signal processing.

Interest Rates: Term Structure and Valuing Bonds

Explores interest rates, term structures, bond valuation, and credit risk impact on bond prices.

Filter Usage

Covers the usage of filters in the EPFL Service Desk environment and managing group assignments.

Advanced Filtering in Professor Recruitment List

Covers advanced filtering techniques in navigating the professor recruitment list.

Advanced Pandas Functions

Covers advanced functions of Pandas, focusing on filtering, labeling, and manipulating dataframes.

Analyze Particles

Covers the process of analyzing particles in images using Fiji software.

Kalman Filtering: Applications in Control and Communication Systems

Explores the applications of Kalman Filtering in control and communication systems, focusing on state estimation and channel estimation.

Kalman Filters: Estimation and Localization

Covers the theory and application of Kalman Filters for estimation and localization in robotics.

Inference Engines: Resolution and Horn Clauses

Covers inference engines based on resolution, Horn clauses, filtering, and unification in artificial intelligence.

Image Processing: Enhancement and Analysis

Explores image processing techniques such as contrast manipulation, enhancement, and sharpening using Fiji software.

Image Processing Techniques

Covers image processing techniques including noise addition, filtering, and image enhancement using various filters and tools.

Adaptive Signal Processing: Filtering & Neural Networks

Explores adaptive signal processing, gradient descent, and the LMS algorithm for efficient filtering and neural network training.

Digital PID Control: Filtering Noisy Signals

Discusses digital PID controllers, noise filtering in feedback controllers, and the challenges of approximating integral and derivative terms.