
Type
Experience
Scope
SVD: 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 MoreAn efficient orientation filter for inertial and inertial/magnetic sensor ar...
This report presents a novel orientation filter applicable to IMUs consisting of tri-axis gyroscopes and accelerometers, and MARG sensor arrays that also include tri-axis magnetometers. The...
See MoreFrequency domain – tutorial 9: frequency response
In this video, the learning objectives are to:1- fully understand the frequency response which forms the foundation of filtering 2- quickly review the common...
See MoreCORRECTION: Bode Plots by Hand: Complex Poles or Zeros
I explain how to determine the straight-line estimate of the Bode Plot for a second order transfer function with a pair of complex poles. This video is a repeat of the last half of the Bode...
See MoreDynamic Behavior and Input Types in Process Control
An introduction to the four types of dynamic behavior and five types of inputs (step, ramp, pulse, impulse, and sinusoidal), and why transfer functions are u...
See MoreData-Driven Control: Balanced Models with ERA
In this lecture, we connect the eigensystem realization algorithm (ERA) to balanced proper orthogonal decomposition (BPOD). In particular, if enough data is collected, then ERA produces...
See MoreTikZ source Code: Switching Manifold
TikZ source Code: Switching Manifold
See MoreMachine Learning Control: Genetic Programming
This lecture explores the use of genetic programming to simultaneously optimize the structure and parameters of an effective control law.
See MoreData-Driven Control: Balancing Example
In this lecture, we give an example of how a change of coordinates can balance the controllability and observability of an input—output system.
See MoreMachine Learning Goals
This lecture discusses the high-level goals of machine learning, and what we want out of our models. Goals include speed and accuracy, along with interpretability, generalizability...
See MoreIMC based PID Design for a First Order Process
IMC based PID Design for a First Order Process
See MoreRL Course by David Silver - Lecture 5: Model Free Control
Dives into On Policy Monte-Carlo Control and Temporal Difference Learning, as well as Off-Policy Learning.
See MoreDiscrete control #1: Introduction and overview
So far I have only addressed designing control systems using the frequency domain, and only with continuous systems. That is, we’ve been working in the S domain with transfer functions. We...
See MoreWorking with Synthetic Data | Deep Learning for Engineers, Part 2
This video covers the first step in deep learning: having access to data. Part of making the decision of whether deep learning is right for your project comes down to the type and amount of...
See MoreSketching Root Locus Part 2
This is the second part of how to sketch a root locus by hand. However instead of following the normal rules for sketching a locus that you'd see in a book, I decided to explain the rules...
See MoreNumerically Calculating Partial Derivatives
In this video we discuss how to calculate partial derivatives of a function using numerical techniques. In other words, these partials are calculated withou...
See MoreMIT 6.S191: Introduction to Deep Learning
MIT's introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep...
See MoreFourier Analysis: Overview
This video presents an overview of the Fourier Transform, which is one of the most important transformations in all of mathematical physics and engineering. This series will introduce the...
See MoreThe Inverse Laplace Transform
In this video we show how to perform the inverse Laplace transform on a signal in the Laplace domain to obtain its equivalent representation in the time doma...
See MoreThe Fourier Transform and Convolution Integrals
This video describes how the Fourier Transform maps the convolution integral of two functions to the product of their respective Fourier Transforms.
See MoreControl Systems Lectures - Transfer Functions
This lecture describes transfer functions and how they are used to simplify modeling of dynamic systems.
See MoreUnderstanding and Sketching Individual Bode Plot Components
In this video we illustrate how 7 types of simple transfer functions contribute to a bode plot. We refer to these as ‘components’ and will cover the followi...
See MorePeter Ponders PID-Fuzzy Logic vs PID
There are many academic and engineering papers showing how good fuzzy logic control is relative to PID control. Every FL vs PID paper I have seen compares...
See MoreDesigning a Lag Compensator with Root Locus
This video walks through a phase lag compensator example using the Root Locus method.
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