Mathematical analysts | Complex analysts
Hermann Hankel (14 February 1839 – 29 August 1873) was a German mathematician. Having worked on mathematical analysis during his career, he is best known for introducing the Hankel transform and the Hankel matrix. (Wikipedia).
Hankel Alternative View of Koopman (HAVOK) Analysis [SHORT]
This video illustrates a new algorithm to decompose chaos into a linear system with intermittent forcing. This is based on the Hankel Alternative View of Koopman (HAVOK) analysis that builds linear regression models on eigen-time-delay coordinates. Chaos as an Intermittently Forced Line
From playlist Research Abstracts from Brunton Lab
Data-Driven Control: Balanced Proper Orthogonal Decomposition
In this lecture, we introduce the balancing proper orthogonal decomposition (BPOD) to approximate balanced truncation for high-dimensional systems. https://www.eigensteve.com/
From playlist Data-Driven Control with Machine Learning
Data-Driven Control: Eigensystem Realization Algorithm Procedure
In this lecture, we describe the eigensystem realization algorithm (ERA) in detail, including step-by-step algorithmic instructions. https://www.eigensteve.com/
From playlist Data-Driven Control with Machine Learning
Hankel Alternative View of Koopman (HAVOK) Analysis [FULL]
This video illustrates a new algorithm to decompose chaos into a linear system with intermittent forcing. This is based on the Hankel Alternative View of Koopman (HAVOK) analysis that builds linear regression models on eigen-time-delay coordinates. Chaos as an Intermittently Forced Line
From playlist Research Abstracts from Brunton Lab
Absolute continuity of limiting spectral distributions of Toeplitz... by Manjunath Krishnapur
PROGRAM: ADVANCES IN APPLIED PROBABILITY ORGANIZERS: Vivek Borkar, Sandeep Juneja, Kavita Ramanan, Devavrat Shah, and Piyush Srivastava DATE & TIME: 05 August 2019 to 17 August 2019 VENUE: Ramanujan Lecture Hall, ICTS Bangalore Applied probability has seen a revolutionary growth in resear
From playlist Advances in Applied Probability 2019
Data-Driven Control: Balanced Truncation and BPOD Example
In this lecture, we explore balanced truncation and BPOD on a numerical example in Matlab. Code: faculty.washington.edu/sbrunton/DataDrivenControl.zip https://www.eigensteve.com/
From playlist Data-Driven Control with Machine Learning
Peter Benner: Matrix Equations and Model Reduction, Lecture 4
Peter Benner from the Max Planck Institute presents: Matrix Equations and Model Reduction; Lecture 4
From playlist Gene Golub SIAM Summer School Videos
Alexander Pushnitski : Rational approximation of functions with logarithmic singularities
Find this video and other talks given by worldwide mathematicians on CIRM's Audiovisual Mathematics Library: http://library.cirm-math.fr. And discover all its functionalities: - Chapter markers and keywords to watch the parts of your choice in the video - Videos enriched with abstracts, b
From playlist Analysis and its Applications
Necmiye Ozay: "A fresh look at some classical system identification methods"
Intersections between Control, Learning and Optimization 2020 "A fresh look at some classical system identification methods" Necmiye Ozay - University of Michigan Abstract: System identification has a long history with several well-established methods, in particular for learning linear d
From playlist Intersections between Control, Learning and Optimization 2020
Linear model for chaotic Lorenz system [HAVOK]
In this short video, we describe how the chaotic Lorenz system may be modeled with a sparse, integer-valued, skew-symmetric, linear system. This is based on the new Hankel Alternative View of Koopman (HAVOK) analysis. Read more about this work: Chaos as an Intermittently Forced Linea
From playlist Research Abstracts from Brunton Lab