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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The Root Locus Method - Introduction

This Root Locus method is a fantastic way of visualizing how the poles of a system move through the S-plane when a single system parameter is varied from 0 to infinity. I show how to...

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Trimming a Model of a Dynamic System Using Numerical Optimization

In this video we show how to find a trim point of a dynamic system using numerical optimization techniques. We generate a cost function that corresponds to ...

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Peter Ponders PID - Root Locus Is Useless

Root Locus is almost worthless. Knowing where the poles are as only 1 gain is changed is not very useful since one only has a limited choices on response. ... See More

Mounting and Configuring the IMU - dRehmFlight VTOL

This video will show you how to verify proper operation of the IMU for dRehmFlight VTOL before your first flight. It will also show you how to correctly mount the IMU to your aircraft. The...

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SVD: Eigenfaces 3 [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 3).

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The Laplace Transform

In this video we show how to perform the Laplace transform on a signal in the time domain to obtain its equivalent representation in the Laplace domain. Top...

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TikZ source Code: Feedforward passivity index

TikZ source Code: Feedforward passivity index

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Control Bootcamp: Example Frequency Response (Bode Plot) for Spring-Mass-Da...

This video shows how to compute and interpret the Bode plot for a simple spring-mass-damper system.

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Standard HW Problem #2: Which is the real open loop transfer function?

In this video, we’ll go through another standard homework problem so you can see how you can apply many of the things you’re learning into a single problem. The question is, we have two...

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Introduction to Bode Plots

In this video we introduce the concept of Bode plots including what they represent, how they are generated, as well as how to use Matlab tools to work with B...

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TikZ source Code: Mobile Robot Slip

TikZ source Code: Mobile Robot Slip

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Machine Learning and Cross-Validation

This lecture discusses the importance of cross-validation to assess models obtained via machine learning.

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Derivation and Solution of Laplace’s Equation

In this video we show how the heat equation can be simplified to obtain Laplace’s equation. We investigate how to solve Laplace’s equation using separation ...

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Data-Driven Control: Error Bounds for Balanced Truncation

In this lecture, we derive error bounds for the balanced truncation.

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Understanding Model Predictive Control, Part 2: What is MPC?

Learn how model predictive control (MPC) works. Using a simple car example, this video provides insight into an MPC controller’s strategy for finding the optimal steering wheel angle to...

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Laplace domain – tutorial 5: Inverse Laplace transform

In this video, we cover inverse Laplace transform which enables us to travel back from Laplace to the time domain. We will learn how to use simple tricks alo...

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Frequency domain – tutorial 3: filtering (periodic signals)

In this video, we learn about filtering which enables us to manipulate the frequency content of a signal. A common filtering application is to preserve desi...

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Machine Learning Course by Andrew Ng

A very comprehensive and detailed course in machine learning , best suited for beginners with knowledge of high school linear mathematics.

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Control Systems Lectures - Closed Loop Control

This lecture discusses the differences between open loop and closed loop control.

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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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Relative Gain Array RGA Analysis

I cover how you can find the relative gain array from the steady state gain array, and interpret the results to determine which input to pair with which outp...

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Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 2 - Given a M...

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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Stanford CS234: Reinforcement Learning | Winter 2019 | Lecture 12 - Fast Rei...

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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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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