
Virtual Laboratory for Vibrations and Control Theory
This virtual lab developed in Matlab Simscape provides an innovative tool for learning and teaching fundamentals of mechanical vibrations including mass-spring-damper systems.
See MoreData-Driven Control: Observer Kalman Filter Identification
In this lecture, we introduce the observer Kalman filter identification (OKID) algorithm. OKID takes natural input--output data from a system and estimates the impulse response, for later...
See MoreKoopman Spectral Analysis (Representations)
In this video, we explore how to obtain finite-dimensional representations of the Koopman operator from data, using regression.
See MoreVelocity & Acceleration in Non-Inertial Reference Frames (Coriolis &...
In this video we derive a mathematical description of velocity and acceleration in non-inertial reference frame. We examine the effect of fictitious forces that are witnessed by observers on...
See MoreSVD: Eigenfaces 4 [Matlab]
This video describes how the singular value decomposition (SVD) can be used to efficiently represent human faces, in the so-called "eigenfaces" (Matlab code, part 4).
See MoreIdentifying Dominant Balance Physics from Data - Jared Callaham
This video illustrates a new algorithm to identify local dominant physical balance relations from multiscale spatiotemporal data.
See MoreStanford CS234: Reinforcement Learning | Winter 2019 | Lecture 16 - Monte Ca...
Professor Emma Brunskill
Assistant Professor, Computer Science
Stanford AI for Human Impact Lab
Stanford Artificial Intelligence Lab
Statistical Machine Learning Group
Data-Driven Control: Balanced Truncation Example
In this lecture, we explore the balanced truncation procedure on an example in Matlab. In particular, we demonstrate the ability of a balancing transformation to make the controllability...
See MoreDiscrete-Time Dynamical Systems
This video shows how discrete-time dynamical systems may be induced from continuous-time systems.
See MoreNumerically Linearizing a Dynamic System
In this video we show how to linearize a dynamic system using numerical techniques. In other words, the linearization process does not require an analytical description of the system. This...
See MoreSingular Value Decomposition (SVD): Mathematical Overview
This video presents a mathematical overview of the singular value decomposition (SVD).
See MoreHow the Flight Controller Code Works - dRehmFlight VTOL
This video will walk you through the flight controller code of dRehmFlight VTOL to give you a better understanding of the contents and structure. The hope is that it will cover almost...
See MoreUnitary Transformations and the SVD [Python]
This video describes how the singular value decomposition (SVD) is related to unitary transformations, with Python code.
See MoreStanford CS234: Reinforcement Learning | Winter 2019 | Lecture 3 - Model-Fr...
Professor Emma Brunskill
Assistant Professor, Computer Science
Stanford AI for Human Impact Lab
Stanford Artificial Intelligence Lab
Statistical Machine Learning Group
RL Course by David Silver - Lecture 4: Model-Free Prediction
An introduction to Monte-Carlo Learning and Temporal Difference Learning
See MoreRL Course by David Silver - Lecture 9: Exploration and Exploitation
An overview of multi-armed bandits, contextual bandits and Markov Decision Processes.
See MoreData-Driven Control: Change of Variables in Control Systems (Correction)
This video corrects a typo in the previous lecture.
See MoreComplex Fourier Series
This video will describe how the Fourier Series can be written efficiently in complex variables.
See MoreSVD: Eigenfaces 1 [Matlab]
This video describes how the singular value decomposition (SVD) can be used to efficiently represent human faces, in the so-called "eigenfaces" (Matlab code, part 1).
See MoreSparse Identification of Nonlinear Dynamics for Model Predictive Control
This lecture shows how to use sparse identification of nonlinear dynamics with control (SINDYc) with model predictive control to control nonlinear systems purely from data.
See MoreStanford CS234: Reinforcement Learning | Winter 2019 | Lecture 13 - Fast Rei...
Professor Emma Brunskill
Assistant Professor, Computer Science
Stanford AI for Human Impact Lab
Stanford Artificial Intelligence Lab
Statistical Machine Learning Group