Control theory | Signal estimation | Linear filters | Nonlinear filters
Moving horizon estimation (MHE) is an optimization approach that uses a series of measurements observed over time, containing noise (random variations) and other inaccuracies, and produces estimates of unknown variables or parameters. Unlike deterministic approaches, MHE requires an iterative approach that relies on linear programming or nonlinear programming solvers to find a solution. MHE reduces to the Kalman filter under certain simplifying conditions. A critical evaluation of the extended Kalman filter and the MHE found that the MHE improved performance at the cost of increased computational expense. Because of the computational expense, MHE has generally been applied to systems where there are greater computational resources and moderate to slow system dynamics. However, in the literature there are some methods to accelerate this method. (Wikipedia).
Teach Astronomy - Galaxy Distance
http://www.teachastronomy.com/ The distances to galaxies are measured by a range of indicators, and the most distant galaxies are only measured using redshift as the distance indicator. Thus we need a model for the expansion of the universe, the Hubble expansion, to estimate the distance
From playlist 19. Galaxies 2
Teach Astronomy - Distance Scale
http://www.teachastronomy.com/ The distance scale in astronomy is a set of measurements that define distances all the way from the solar system to the most remote galaxies. Conceptually it's a pyramid with nearby methods being direct and fairly accurate while the errors accumulate and gro
From playlist 19. Galaxies 2
Gravitation (13 of 17) Orbital Velocity at the Surface of the Earth
This videos explains how to determine the velocity that an object, one meter above the Earth's surface, must be projected horizontally so that it will go all of the way around the Earth and come back to the same place. Calculate orbital velocity one meter above the Earth's surface. The o
From playlist Gravitation: Orbital Velocity, Orbital Period, Potential Energy, Kinetic Energy, Mass and Weight
Determine when a particle is moving down from a position graph
Keywords 👉 Learn how to solve particle motion problems. Particle motion problems are usually modeled using functions. Now, when the function modeling the position of the particle is given with respect to the time, we find the speed function of the particle by differentiating the function
From playlist Particle Motion Problems
Two Dimensional Motion (2 of 4) Worked Example
For projectile motion shows how to determine the maximum height, the time in the air and the distance traveled for an object that is projected with a known initial velocity at a known angle above the horizon. You can see a listing of all my videos at my website, http://www.stepbystepscien
From playlist Mechanics
Determine when a particle's speed is increasing from a graph
Keywords 👉 Learn how to solve particle motion problems. Particle motion problems are usually modeled using functions. Now, when the function modeling the position of the particle is given with respect to the time, we find the speed function of the particle by differentiating the function
From playlist Determine Increasing or Decreasing Function From a Table
Teach Astronomy - Distance Indicators
http://www.teachastronomy.com/ Any property of a star or galaxy that can be used to measure distance is called a distance indicator. In astronomy the best distance indicators have a clear physical or astrophysical basis and are not purely empirically determined. Within the solar system,
From playlist 19. Galaxies 2
Learn to find the average acceraltion of a particle not given in a table
Keywords 👉 Learn how to solve particle motion problems. Particle motion problems are usually modeled using functions. Now, when the function modeling the position of the particle is given with respect to the time, we find the speed function of the particle by differentiating the function
From playlist Determine Increasing or Decreasing Function From a Table
Describes what acceleration is in physics, how to calculate acceleration and how to determine if an object is speeding up, slowing down or moving at a constant velocity based on the direction of it velocity and acceleration vectors You can see a listing of all my videos at my website, http
From playlist Motion Graphs; Position and Velocity vs. Time
Guilherme Mazanti: "Second-order local minimal-time mean field games"
High Dimensional Hamilton-Jacobi PDEs 2020 Workshop III: Mean Field Games and Applications "Second-order local minimal-time mean field games" Guilherme Mazanti - CentraleSupélec Abstract: Motivated by the problem of proposing mean field game models for crowd motion, this talk considers a
From playlist High Dimensional Hamilton-Jacobi PDEs 2020
From playlist CS294-112 Deep Reinforcement Learning Sp17
sktime - A Unified Toolbox for ML with Time Series
This tutorial is about sktime - a unified framework for machine learning with time series. sktime features various time series algorithms and modular tools for pipelining, ensembling and tuning. You will learn how to use, combine and evaluate different algorithms on real-world data sets an
From playlist Python
Stanford Seminar - Safe and Robust Perception-Based Control
Sarah Dean UC Berkeley February 21, 2020 Machine learning provides a promising path to distill information from high dimensional sensors like cameras -- a fact that often serves as motivation for merging learning with control. This talk aims to provide rigorous guarantees for systems with
From playlist Stanford AA289 - Robotics and Autonomous Systems Seminar
Primordial Black Hole DM - II (Lecture 2) by Yacine Ali Haimoud
PROGRAM LESS TRAVELLED PATH OF DARK MATTER: AXIONS AND PRIMORDIAL BLACK HOLES (ONLINE) ORGANIZERS: Subinoy Das (IIA, Bangalore), Koushik Dutta (IISER, Kolkata / SINP, Kolkata), Raghavan Rangarajan (Ahmedabad University) and Vikram Rentala (IIT Bombay) DATE: 09 November 2020 to 13 Novemb
From playlist Less Travelled Path of Dark Matter: Axions and Primordial Black Holes (Online)
Dream to Control: Learning Behaviors by Latent Imagination
Dreamer is a new RL agent by DeepMind that learns a continuous control task through forward-imagination in latent space. https://arxiv.org/abs/1912.01603 Videos: https://dreamrl.github.io/ Abstract: Learned world models summarize an agent's experience to facilitate learning complex behav
From playlist Reinforcement Learning
Numerical relativity: Survey of results by Harald Pfeiffer
PROGRAM: GRAVITATIONAL WAVE ASTROPHYSICS (ONLINE) ORGANIZERS : Parameswaran Ajith, K. G. Arun, Sukanta Bose, Bala R. Iyer, Resmi Lekshmi and B Sathyaprakash DATE: 18 May 2020 to 22 May 2020 VENUE: Online Due to the ongoing COVID-19 pandemic, the original program has been cancelled. Howe
From playlist Gravitational Wave Astrophysics (Online) 2020
Deriving Hawking's most famous equation: What is the temperature of a black hole?
Black holes are perhaps the most enigmatic objects in the universe. Popularised in movies and science fiction, they evoke the magic and mystery of our universe and provide inspiration for those looking to make their mark in the world of academic physics. But what exactly is a black hole? A
From playlist Relativity
Lightning Talks - Chi Jin, Lin Yang, Alec Koppel, Karan Singh, Nataly Brukhim
Workshop on New Directions in Reinforcement Learning and Control Topic:Lightning Talks Speaker: Chi Jin, Lin Yang, Alec Koppel, Karan Singh, Nataly Brukhim Date: November 8, 2019 For more video please visit http://video.ias.edu
From playlist Mathematics
Given a table of velocity determine when a particles speed is increasing
Keywords 👉 Learn how to solve particle motion problems. Particle motion problems are usually modeled using functions. Now, when the function modeling the position of the particle is given with respect to the time, we find the speed function of the particle by differentiating the function
From playlist Determine Increasing or Decreasing Function From a Table