Numerical integration (quadrature)

Adaptive quadrature is a numerical integration method in which the integral of a function is approximated using static quadrature rules on adaptively refined subintervals of the region of integration. Generally, adaptive algorithms are just as efficient and effective as traditional algorithms for "well behaved" integrands, but are also effective for "badly behaved" integrands for which traditional algorithms may fail. (Wikipedia).

Adaptive Quadrature | Lecture 41 | Vector Calculus for Engineers

What is adaptive quadrature? Join me on Coursera: https://www.coursera.org/learn/numerical-methods-engineers Lecture notes at http://www.math.ust.hk/~machas/numerical-methods-for-engineers.pdf Subscribe to my channel: http://www.youtube.com/user/jchasnov?sub_confirmation=1

From playlist Numerical Methods for Engineers

Gaussian Quadrature | Lecture 40 | Numerical Methods for Engineers

An explanation of Gaussian quadrature. An example of how to calculate the weights and nodes for two-point Legendre-Gauss quadrature. Join me on Coursera: https://www.coursera.org/learn/numerical-methods-engineers Lecture notes at http://www.math.ust.hk/~machas/numerical-methods-for-engi

From playlist Numerical Methods for Engineers

Adding Vectors Geometrically: Dynamic Illustration

Link: https://www.geogebra.org/m/tsBer5An

From playlist Trigonometry: Dynamic Interactives!

This video introduces the concept of phased arrays. An array refers to multiple sensors, arranged in some configuration, that act together to produce a desired sensor pattern. With a phased array, we can electronically steer that pattern without having to physically move the array simply b

From playlist Understanding Phased Array Systems and Beamforming

Computational Methods for Numerical Relativity, Part 3 Frans Pretorius

Computational Methods for Numerical Relativity, Part 3 Frans Pretorius Princeton University July 22, 2009

From playlist PiTP 2009

An introduction to Beamforming

This video talks about how we actually have more control over the shape of the beam than just adding additional elements or adjusting the position and orientation of the elements. We can also adjust the gain of the signal to each element and apply phase unevenly to each element, and that

From playlist Understanding Phased Array Systems and Beamforming

Ditch the Tricks: Estimating Trig Ratios: Conceptual Quiz Questions

Link: https://www.geogebra.org/m/F5a9GDd6

From playlist Trigonometry: Dynamic Interactives!

Engineering CEE 20: Engineering Problem Solving. Lecture 24

UCI CIvil & Environmental Engineering 20 Engineering Problem Solving (Spring 2013) Lec 24. Engineering Problem Solving View the complete course: http://ocw.uci.edu/courses/cee_20_introduction_to_computational_engineering_problem_solving.html Instructor: Jasper Alexander Vrugt, Ph.D. Licen

From playlist Engineering CEE 20: Engineering Problem Solving

DDPS | Towards reliable, efficient, and automated model reduction of parametrized nonlinear PDEs

Description: Many engineering tasks, such as parametric study and uncertainty quantification, require rapid and reliable solution of partial differential equations (PDEs) for many different configurations. In this talk, we consider goal-oriented model reduction of parametrized nonlinear PD

From playlist Data-driven Physical Simulations (DDPS) Seminar Series

Continuous multi-fidelity optimization

This video is #8 in the Adaptive Experimentation series presented at the 18th IEEE Conference on eScience in Salt Lake City, UT (October 10-14, 2022). In this video, Sterling Baird @sterling-baird presents on continuous multifidelity optimization. Continuous multi-fidelity optimization is

From playlist Optimization tutorial

Cyclic Quadrilateral: Proof Hint!

Link: https://www.geogebra.org/m/KYdypjws

From playlist Geometry: Dynamic Interactives!

Tzanio Kolev - Meso and Macroscale Modeling 1 - IPAM at UCLA

Recorded 15 March 2023. Tzanio Kolev of Lawrence Livermore National Laboratory presents "Meso and Macroscale Modeling 1" at IPAM's New Mathematics for the Exascale: Applications to Materials Science Tutorials. Learn more online at: http://www.ipam.ucla.edu/programs/workshops/new-mathematic

From playlist 2023 New Mathematics for the Exascale: Applications to Materials Science Tutorials

Lin Lin - Large scale hybrid DFT functionals: fast algorithms and finite-size effects - IPAM at UCLA

Recorded 02 May 2022. Lin Lin of the University of California, Berkeley, Mathematics, presents "Large scale hybrid DFT functionals: fast algorithms and finite-size effects" at IPAM's Large-Scale Certified Numerical Methods in Quantum Mechanics Workshop. Abstract: I will discuss recent prog

From playlist 2022 Large-Scale Certified Numerical Methods in Quantum Mechanics

CMPSC/Math 451: Feb. 23, 2015. Adaptive Simpson's Rule. Wen Shen

Wen Shen, Penn State University. Lectures are based on my book: "An Introduction to Numerical Computation", published by World Scientific, 2016. See promo video: https://youtu.be/MgS33HcgA_I

From playlist Numerical Computation spring 2015. Wen Shen. Penn State University.

Daniele Avitabile - Projection methods for neurobiological networks

---------------------------------- Institut Henri Poincaré, 11 rue Pierre et Marie Curie, 75005 PARIS http://www.ihp.fr/ Rejoingez les réseaux sociaux de l'IHP pour être au courant de nos actualités : - Facebook : https://www.facebook.com/InstitutHenriPoincare/ - Twitter : https://twitter

From playlist Workshop "Workshop on Mathematical Modeling and Statistical Analysis in Neuroscience" - January 31st - February 4th, 2022

FFT based spectral Ewald methods as an alternative to multipole methods – A.-K. Tornberg – ICM2018

Numerical Analysis and Scientific Computing Invited Lecture 15.5 FFT based spectral Ewald methods as an alternative to fast multipole methods Anna-Karin Tornberg Abstract: In this paper, we review a set of fast and spectrally accurate methods for rapid evaluation of three dimensional ele

From playlist Numerical Analysis and Scientific Computing

Scott Field - Gravitational Wave Parameter Estimation with Compressed Likelihood Evaluations

Recorded 17 November 2021. Scott Field of the University of Massachusetts Dartmouth presents "Gravitational Wave Parameter Estimation with Compressed Likelihood Evaluations" at IPAM's Workshop III: Source inference and parameter estimation in Gravitational Wave Astronomy. Abstract: One of

From playlist Workshop: Source inference and parameter estimation in Gravitational Wave Astronomy

Composite Quadrature Rules | Lecture 39 | Numerical Methods for Engineers

Composite quadrature rules (numerical integration) using the trapezoidal rule and Simpson's rule. Join me on Coursera: https://www.coursera.org/learn/numerical-methods-engineers Lecture notes at http://www.math.ust.hk/~machas/numerical-methods-for-engineers.pdf Subscribe to my channel:

From playlist Numerical Methods for Engineers