Gentle Introduction to Modeling with Matrices and Vectors: A Probabilistic Weather Model
This video gives an intro example of how we model complex systems that change in time, using matrices and vectors. Specifically, I build a toy model for the weather, where the probability of the weather today being "(R)ainy", "(N)ice", or "(C)loudy" is stored in a vector [R, N, C]. This probability of the weather being in one of these states tomorrow is then updated by multiplying this vector by a probability matrix.
Code examples are given in Python and Matlab.
Playlist: https://www.youtube.com/playlist?list=PLMrJAkhIeNNTYaOnVI3QpH7jgULnAmvPA
Course Website: http://faculty.washington.edu/sbrunton/me564/
@eigensteve on Twitter
eigensteve.com
databookuw.com
This video was produced at the University of Washington
%%% CHAPTERS %%%
0:00 Overview
1:07 Building a simple weather model
5:00 Modeling the state as a vector
6:50 Writing the dynamical system update rule as a matrix
14:07 Matlab code example
23:43 Python code example
38:24 Teaser of how to make system more realistic
Видео Gentle Introduction to Modeling with Matrices and Vectors: A Probabilistic Weather Model канала Steve Brunton
Code examples are given in Python and Matlab.
Playlist: https://www.youtube.com/playlist?list=PLMrJAkhIeNNTYaOnVI3QpH7jgULnAmvPA
Course Website: http://faculty.washington.edu/sbrunton/me564/
@eigensteve on Twitter
eigensteve.com
databookuw.com
This video was produced at the University of Washington
%%% CHAPTERS %%%
0:00 Overview
1:07 Building a simple weather model
5:00 Modeling the state as a vector
6:50 Writing the dynamical system update rule as a matrix
14:07 Matlab code example
23:43 Python code example
38:24 Teaser of how to make system more realistic
Видео Gentle Introduction to Modeling with Matrices and Vectors: A Probabilistic Weather Model канала Steve Brunton
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
Data-Driven Control: The Goal of Balanced Model ReductionRobust Regression with the L1 Norm [Python]Koopman Spectral Analysis (Multiscale systems)The Wave Equation and Slack Line PhysicsInterpretable Aeroelastic Models for Control at Insect ScaleExtremum Seeking Control in SimulinkSystems of Differential Equations with Forcing: Example in Control TheoryAirfoil pitching about leading-edge (+/- 20 deg, Re=100), with FTLE visualizationHankel Alternative View of Koopman (HAVOK) Analysis [FULL]Engineering Math Pre-Req: Quick and Dirty Introduction to MatlabData-Driven Control: Error Bounds for Balanced TruncationSVD: Eigenfaces 4 [Matlab]Particles starting near positive-time LCS attract onto negative-time LCSMeasure-preserving EDMD: A 4-line structure-preserving & convergent DMD algorithm!Validation of forward-time FTLE field for vortex sheddingData-Driven Control: Balanced Models with ERASVD: Importance of Alignment [Matlab]Neural Networks and Deep LearningData-Driven Control: BPOD and Output ProjectionSolving PDEs with the FFT, Part 2 [Matlab]Koopman Spectral Analysis (Continuous Spectrum)