In this video, I define the concept of orthogonal projection of a vector on a line (and on more general subspaces), derive a very nice formula for it, and show why orthogonal projections are so useful. You might even see the hugging formula again. Enjoy! This is the second part of the ort
From playlist Orthogonality
11J Orthogonal Projection of a Vector
The orthogonal projection of one vector along another.
From playlist Linear Algebra
Determine if the Vectors are Orthogonal
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Determine if the Vectors are Orthogonal
From playlist Calculus
Linear Algebra 7.1 Orthogonal Matrices
My notes are available at http://asherbroberts.com/ (so you can write along with me). Elementary Linear Algebra: Applications Version 12th Edition by Howard Anton, Chris Rorres, and Anton Kaul A. Roberts is supported in part by the grants NSF CAREER 1653602 and NSF DMS 2153803.
From playlist Linear Algebra
11H Orthogonal Projection of a Vector
The orthogonal projection of one vector along another.
From playlist Linear Algebra
This is the first video of a linear algebra-series on orthogonality. In this video, I define the notion of orthogonal sets, then show that an orthogonal set without the 0 vector is linearly independent, and finally I show that it's easy to calculate the coordinates of a vector in terms of
From playlist Orthogonality
In this last part of the orthogonality extravaganza, I show how to use our orthogonality-formula to find the full Fourier series of a function. I also show to what function the Fourier series converges too. In a future video, I'll show you how to find the Fourier sine/cosine series of a fu
From playlist Orthogonality
Find an Orthogonal Projection of a Vector Onto a Line Given an Orthogonal Basis (R2)
This video explains how t use the orthogonal projection formula given subset with an orthogonal basis. The distance from the vector to the line is also found.
From playlist Orthogonal and Orthonormal Sets of Vectors
Achieving the Heisenberg limit in quantum metrology (...) - L. Jiang - Workshop 1 - CEB T2 2018
Liang Jiang (Univ. Yale) / 16.05.2018 Achieving the Heisenberg limit in quantum metrology using quantum error correction Quantum metrology has many important applications in science and technology, ranging from frequency spectroscopy to gravitational wave detection. Quantum mechanics imp
From playlist 2018 - T2 - Measurement and Control of Quantum Systems: Theory and Experiments
Lec 20 | MIT 6.450 Principles of Digital Communications I, Fall 2006
Lecture 20: Introduction of wireless communication View the complete course at: http://ocw.mit.edu/6-450F06 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.450 Principles of Digital Communications, I Fall 2006
Neuroscience source separation 2a: Spatial separation
This is part two of a three-part lecture series I taught in a masters-level neuroscience course in fall of 2020 at the Donders Institute (the Netherlands). The lectures were all online in order to minimize the spread of the coronavirus. That's good for you, because now you can watch the en
From playlist Neuroscience source separation (3-part lecture series)
GED for spatial filtering and dimensionality reduction
Generalized eigendecomposition is a powerful method of spatial filtering in order to extract components from the data. You'll learn the theory, motivations, and see a few examples. Also discussed is the dangers of overfitting noise and few ways to avoid it. The video uses files you can do
From playlist OLD ANTS #9) Matrix analysis
MIT MIT 6.003 Signals and Systems, Fall 2011 View the complete course: http://ocw.mit.edu/6-003F11 Instructor: Dennis Freeman License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.003 Signals and Systems, Fall 2011
Understanding the Inner Workings of the Fourier Transform
In this video, I am going to attempt to explain the inner workings of the Fourier transform. This video is a condensed and combined version of the Fourier Transform series I created in Korean on my Youtube channel. I submitted this video to participate in the #3b1b #SoME1 math contest. Tha
From playlist Summer of Math Exposition Youtube Videos
Daniel Roberts: "Deep learning as a toy model of the 1/N-expansion and renormalization"
Machine Learning for Physics and the Physics of Learning 2019 Workshop IV: Using Physical Insights for Machine Learning "Deep learning as a toy model of the 1/N-expansion and renormalization" Daniel Roberts - Diffeo Institute for Pure and Applied Mathematics, UCLA November 20, 2019
From playlist Machine Learning for Physics and the Physics of Learning 2019
Lecture 15 | Introduction to Linear Dynamical Systems
Professor Stephen Boyd, of the Electrical Engineering department at Stanford University, lectures on inputs and outputs of linear dynamical systems, as well as symmetric matrices for the course, Introduction to Linear Dynamical Systems (EE263). Introduction to applied linear algebra and
From playlist Lecture Collection | Linear Dynamical Systems
Linear Algebra 3.3 Orthogonality
My notes are available at http://asherbroberts.com/ (so you can write along with me). Elementary Linear Algebra: Applications Version 12th Edition by Howard Anton, Chris Rorres, and Anton Kaul
From playlist Linear Algebra
Lecture 20 | The Fourier Transforms and its Applications
Lecture by Professor Brad Osgood for the Electrical Engineering course, The Fourier Transforms and its Applications (EE 261). Professor Osgood continues his lecture on the Discrete Fourier Transform. The Fourier transform is a tool for solving physical problems. In this course the emph
From playlist Lecture Collection | The Fourier Transforms and Its Applications