Linearizing Nonlinear Differential Equations Near a Fixed Point
This video describes how to analyze fully nonlinear differential equations by analyzing the linearized dynamics near a fixed point. Most of our powerful solution techniques for ODEs are only valid for linear systems, so this is an important strategy for studying nonlinear systems. This
From playlist Engineering Math: Differential Equations and Dynamical Systems
(8.1) A General Approach to Nonlinear Differential Questions
This video briefly describes the approach to gaining information about the solution to nonlinear differential equations. https://mathispower4u.com
From playlist Differential Equations: Complete Set of Course Videos
C52 Introduction to nonlinear DEs
A first look at nonlinear differential equations. In this first video examples are shown of equations that still have explicit solutions.
From playlist Differential Equations
Intro to Linear Systems: 2 Equations, 2 Unknowns - Dr Chris Tisdell Live Stream
Free ebook http://tinyurl.com/EngMathYT Basic introduction to linear systems. We discuss the case with 2 equations and 2 unknowns. A linear system is a mathematical model of a system based on the use of a linear operator. Linear systems typically exhibit features and properties that ar
From playlist Intro to Linear Systems
(ML 9.2) Linear regression - Definition & Motivation
Linear regression arises naturally from a sequence of simple choices: discriminative model, Gaussian distributions, and linear functions. A playlist of these Machine Learning videos is available here: http://www.youtube.com/view_play_list?p=D0F06AA0D2E8FFBA
From playlist Machine Learning
(ML 13.6) Graphical model for Bayesian linear regression
As an example, we write down the graphical model for Bayesian linear regression. We introduce the "plate notation", and the convention of shading random variables which are being conditioned on.
From playlist Machine Learning
B27 Introduction to linear models
Now that we finally now some techniques to solve simple differential equations, let's apply them to some real-world problems.
From playlist Differential Equations
(ML 9.1) Linear regression - Nonlinearity via basis functions
Introduction to linear regression. Basis functions can be used to capture nonlinearities in the input variable. A playlist of these Machine Learning videos is available here: http://www.youtube.com/view_play_list?p=D0F06AA0D2E8FFBA
From playlist Machine Learning
For the latest information, please visit: http://www.wolfram.com Speaker: Suba Thomas In Mathematica 10, a full suite of functions for analyzing and designing nonlinear control systems was introduced. This talk showcases the workflow for designing controllers for nonlinear systems using
From playlist Wolfram Technology Conference 2014
Adaptive, Gain-Scheduled and Nonlinear Model Predictive Control | Understanding MPC, Part 4
This video explains the type of MPC controller you can use based on your plant model, constraints, and cost function. - Model Predictive Control Toolbox: http://bit.ly/2xgwWvN- - What Is Model Predictive Control Toolbox?: http://bit.ly/2xfEe2M The available options include the linear ti
From playlist Understanding Model Predictive Control
System Identification: Full-State Models with Control
This lecture provides an overview of modern data-driven regression methods for linear and nonlinear system identification, based on the dynamic mode decomposition (DMD), Koopman theory, and the sparse identification of nonlinear dynamics (SINDy). https://www.eigensteve.com/
From playlist Data-Driven Control with Machine Learning
EXTRA MATH 11D: Extended regression modelling: Multiple input, non-linear relations and categorical/
Forelæsning med Per B. Brockhoff. Kapitler: 00:00 - Linear; 06:40 - Non-Linear; 09:00 - Non-Linear Regression; 11:25 - Models For Categorical Data;
From playlist DTU: Introduction to Statistics | CosmoLearning.org
Sparse Identification of Nonlinear Dynamics for Model Predictive Control
This lecture shows how to use sparse identification of nonlinear dynamics with control (SINDYc) with model predictive control to control nonlinear systems purely from data. Sparse identification of nonlinear dynamics for model predictive control in the low-data limit. E. Kaiser, J. N. K
From playlist Data-Driven Control with Machine Learning
Lec 1 | MIT Finite Element Procedures for Solids and Structures, Nonlinear Analysis
Lecture 1: Introduction to nonlinear analysis Instructor: Klaus-Jürgen Bathe View the complete course: http://ocw.mit.edu/RES2-002S10 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT Nonlinear Finite Element Analysis
Data-Driven Control: Linear System Identification
Overview lecture on linear system identification and model reduction. This lecture discusses how we obtain reduced-order models from data that optimally capture input--output dynamics. https://www.eigensteve.com/
From playlist Data-Driven Control with Machine Learning
MFEM Workshop 2022 | Reduced Order Modeling for FE Simulations with MFEM & libROM
The LLNL-led MFEM (Modular Finite Element Methods) project provides high-order mathematical calculations for large-scale scientific simulations. The project’s second community workshop was held on October 25, 2022, with participants around the world. Learn more about MFEM at https://mfem.o
From playlist MFEM Community Workshop 2022
System Identification: Sparse Nonlinear Models with Control
This lecture explores an extension of the sparse identification of nonlinear dynamics (SINDy) algorithm to include inputs and control. The resulting SINDY with control (SINDYc) can be used with model predictive control for nonlinear systems. Sparse identification of nonlinear dynamics
From playlist Data-Driven Control with Machine Learning
Linear versus Nonlinear Differential Equations
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Linear versus Nonlinear Differential Equations
From playlist Differential Equations
Nonlinear Model Predictive Control Design | Understanding MPC, Part 8
Learn how to design a nonlinear MPC controller for an automated driving application with Model Predictive Control Toolbox™ and Embotech FORCESPRO solvers. - Lane following using nonlinear model predictive control: https://bit.ly/3m3g19u The demonstration shows how to use the nonlinear M
From playlist Understanding Model Predictive Control