Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 15 - Batch Re...

Professor Emma Brunskill
Assistant Professor, Computer Science
Stanford AI for Human Impact Lab
Stanford Artificial Intelligence Lab
Statistical Machine Learning Group

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Deploying Deep Learning Models | Deep Learning for Engineers, Part 5

This video covers the additional work and considerations you need to think about once you have a deep neural network that can classify your data. We need to consider that the trained network...

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Drone Simulation and Control, Part 5: Tuning the PID controller

In the last video, we learned how accurate, nonlinear models are great for simulation but they don’t lend themselves well to linear analysis and design. This video takes the nonlinear model...

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Principal Component Analysis (PCA)

Principal component analysis (PCA) is a workhorse algorithm in statistics, where dominant correlation patterns are extracted from high-dimensional data.

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Peter Ponders PID - Cascade Control Part2

The inner loop pole locations and gains are calculated first so the inner loop pole locations are determined by the user. The outer loop poles are still pla...

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Building a Matlab/Simulink Model of an Aircraft: the Research Civil Aircraft...

In this video we implement the RCAM model as a Matlab script that is called from a Simulink model. The result is a fully encapsulated Simulink model of a no...

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Computing the DFT Matrix

This video discusses how to compute the Discrete Fourier Transform (DFT) matrix in Matlab and Python. In practice, the DFT should usually be computed using the fast Fourier transform (FFT)...

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SOPDT Sliding Mode Control ( SMC ) with Smith Predictor

I made this simulation SMC with Smith predictor just to see how it would work. I am not a process control guy but so many people struggle with temperature c... See More

Introduction to Full State Feedback Control

In this video we introduce the concept of a full state feedback controller. We discuss how to use this system to place the eigenvalues of the closed loop sys...

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The Fast Fourier Transform Algorithm

Here I discuss the Fast Fourier Transform (FFT) algorithm, one of the most important algorithms of all time.

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Computing Euler Angles: Tracking Attitude Using Quaternions

 

In this video we continue our discussion on how to track the attitude of a body in space using quaternions. The quaternion method is similar to the Euler Kinematical Equations and Poisson...

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Understanding Sensor Fusion and Tracking, Part 3: Fusing a GPS and IMU to Es...

This video continues our discussion on using sensor fusion for positioning and localization by showing how we can use a GPS and an IMU to estimate and object’s orientation and position. We...

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Final Value Theorem

In this video we discuss the Final Value Theorem. Given a signal in the Laplace domain, this allows us to predict the steady state value of the signal in th...

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Lecture 12: Steady state error

In this video, steady state error has been explained See More

Randomized Singular Value Decomposition (SVD)

This video describes how to use recent techniques in randomized linear algebra to efficiently compute the singular value decomposition (SVD) for extremely large matrices.

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Singular Value Decomposition (SVD): Mathematical Overview

This video presents a mathematical overview of the singular value decomposition (SVD).

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Control Systems Lectures - Transfer Functions

This lecture describes transfer functions and how they are used to simplify modeling of dynamic systems.

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PID Control with Posicast Control 8 - ( In English )

This is the follow up of PID Control with Posicast ( Part II )

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Using Root Locus to Meet Performance Requirements

In this video we investigate how to use the root locus technique to design a controller that meets certain performance specifications.Topics and timestamps:(...

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Lecture 17: Introduction to Compensators/Controllers

This video introduces compensators or controllers. The 3 basic control actions - proportional, derivative and integral - have been discussed. Also discussed ... See More

SVD: Importance of Alignment [Matlab]

This video describes the importance of aligning data when using the singular value decomposition (SVD) (Matlab code).

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Time domain - tutorial 3: signal transformations

In this video, we learn how different transformations can change the signal shape. Specifically, we cover time shifting & scaling as well as amplitude shift...

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Koopman Spectral Analysis (Representations)

In this video, we explore how to obtain finite-dimensional representations of the Koopman operator from data, using regression.

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Linear Regression 2 [Python]

This video describes how the singular value decomposition (SVD) can be used for linear regression in Python (part 2).

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Controllability and the Discrete-Time Impulse Response [Control Bootcamp]

This lecture derives the impulse response for a discrete-time system and relates this to the controllability matrix.

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