Noise (electronics)

Simulation noise

Simulation noise is a function that creates a divergence-free vector field. This signal can be used in artistic simulations for the purposes of increasing the perception of extra detail. The function can be calculated in three dimensions by dividing the space into a regular lattice grid. With each edge is associated a random value, indicating a rotational component of material revolving around the edge. By following rotating material into and out of faces, one can quickly sum the flux passing through each face of the lattice. Flux values at lattice faces are then interpolated to create a field value for all positions. Perlin noise is the earliest form of , which has become very popular in computer graphics. Perlin Noise is not suited for simulation because it is not divergence-free. Noises based on lattices, such as simulation noise and Perlin noise, are often calculated at different frequencies and summed together to form band-limited fractal signals. Other approaches developed later that use vector calculus identities to produce divergence free fields, such as "Curl-Noise" as suggested by Robert Bridson, and "Divergence-Free Noise" due to Ivan DeWolf. These often require calculation of lattice noise gradients, which sometimes are not readily available. A naive implementation would call a lattice noise function several times to calculate its gradient, resulting in more computation than is strictly necessary. Unlike these noises, simulation noise has a geometric rationale in addition to its mathematical properties. It simulates vortices scattered in space, to produce its pleasing aesthetic. (Wikipedia).

Video thumbnail

Aircraft landing gear air flow supercomputer simulation - NASA Ames Research Center

[video: NASA Ames Research Center] During aircraft landing, noise from the airframe can be greater than the engine noise? Supercomputer simulations (like this one) help us understand the changes in air flow that contribute to airframe noise. Learn more: https://go.nasa.gov/2if70cs #SC17

From playlist Stuff I like from others

Video thumbnail

Time Series Talk : White Noise

Intro to white noise in time series analysis

From playlist Time Series Analysis

Video thumbnail

What is signal and what is noise?

This lecture discusses the distinction between "signal" and "noise" -- and important definition when working with large or complex datasets. This video is part of an online course called "Simulate, understand, & visualize data like a data scientist." The course includes 3+ hours of video

From playlist Simulate, understand, and visualize data

Video thumbnail

What is Sound? - Quickly Discover What Sound Really Is

What is Sound? This simple demonstration visually shows how sound waves are produced from a vibrating surface. A frequency generator is hooked up to a power amplifier, and the resultant signal is used to drive a loudspeaker. The signal is also sent to an oscilloscope. After listen

From playlist Physics Demonstrations

Video thumbnail

What Is White Noise?

Jonathan defines what white noise actually is and how it's used to mask other annoying sounds. Learn more at HowStuffWorks.com: http://science.howstuffworks.com/question47.htm Share on Facebook: http://goo.gl/n7YNrZ Share on Twitter: http://goo.gl/Fq9InS Subscribe: http://goo.gl/ZYI7Gt V

From playlist Episodes hosted by Jonathan

Video thumbnail

New algorithm helps create realistic sound for VR

Read more: https://stanford.io/2yl2wsm Producers use sound effects to enhance the realism of movies and video games, but there has so far been no practical way to generate realistic sounds in response to unscripted actions by characters in virtual environments. At SIGGRAPH 2019, Stanford

From playlist Engineering in Action

Video thumbnail

Learn how to create "pink" noise

Pink noise, also called 1/f noise or fractal noise, is used to model many real-world phenomena. Learn how to simulate pink noise! You can download the MATLAB code here: http://sincxpress.com/MXC_prodata_makePinkishNoise.m This video is part of an online course called "Simulate, understa

From playlist Simulate, understand, and visualize data

Video thumbnail

Sound waves interference!

In this video i demonstrate sound waves interference and standing waves from loudspeaker used sound sensor. The frequency on loudspeaker is about 5500Hz. Enjoy!!!

From playlist WAVES

Video thumbnail

Active Noise Cancellation – From Modeling to Real-Time Prototyping

Active noise control (ANC), also known as active noise cancellation, attempts to cancel unwanted sound using destructive interference. ANC systems use adaptive digital filtering to synthesize a sound wave with the same amplitude as the unwanted signal, but with inverted phase. This video f

From playlist Real-Time Audio Prototyping

Video thumbnail

Markov processes and applications-4 by Hugo Touchette

PROGRAM : BANGALORE SCHOOL ON STATISTICAL PHYSICS - XII (ONLINE) ORGANIZERS : Abhishek Dhar (ICTS-TIFR, Bengaluru) and Sanjib Sabhapandit (RRI, Bengaluru) DATE : 28 June 2021 to 09 July 2021 VENUE : Online Due to the ongoing COVID-19 pandemic, the school will be conducted through online

From playlist Bangalore School on Statistical Physics - XII (ONLINE) 2021

Video thumbnail

Lecture 18 - Continous State MDP & Model Simulation | Stanford CS229: Machine Learning (Autumn 2018)

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/3njDdzN Andrew Ng Adjunct Professor of Computer Science https://www.andrewng.org/ To follow along with the course schedule and syllabus, visit: http://cs229.sta

From playlist Stanford CS229: Machine Learning Full Course taught by Andrew Ng | Autumn 2018

Video thumbnail

Simulating data to understand analysis methods

This video lesson is part of a complete course on neuroscience time series analyses. The full course includes - over 47 hours of video instruction - lots and lots of MATLAB exercises and problem sets - access to a dedicated Q&A forum. You can find out more here: https://www.udemy.

From playlist NEW ANTS #1) Introductions

Video thumbnail

Markov processes and applications-3 by Hugo Touchette

PROGRAM : BANGALORE SCHOOL ON STATISTICAL PHYSICS - XII (ONLINE) ORGANIZERS : Abhishek Dhar (ICTS-TIFR, Bengaluru) and Sanjib Sabhapandit (RRI, Bengaluru) DATE : 28 June 2021 to 09 July 2021 VENUE : Online Due to the ongoing COVID-19 pandemic, the school will be conducted through online

From playlist Bangalore School on Statistical Physics - XII (ONLINE) 2021

Video thumbnail

Ivan Pedro Lobato Hoyos - Application of machine learning to electron microscopy data - IPAM at UCLA

Recorded 25 October 2022. Ivan Pedro Lobato Hoyos of the University of Antwerp presents "Application of machine learning to electron microscopy data" at IPAM's Mathematical Advances for Multi-Dimensional Microscopy Workshop. Abstract: Recent advances in the data acquisition process in the

From playlist 2022 Mathematical Advances for Multi-Dimensional Microscopy

Video thumbnail

Stochastic modelling of geophysical flows - Mémin - Workshop 2 - CEB T3 2019

Mémin (INRIA, FR) / 13.11.2019 Stochastic modelling of geophysical flows ---------------------------------- Vous pouvez nous rejoindre sur les réseaux sociaux pour suivre nos actualités. Facebook : https://www.facebook.com/InstitutHenriPoincare/ Twitter : https://twitter.com/InHe

From playlist 2019 - T3 - The Mathematics of Climate and the Environment

Video thumbnail

Stephen Green - Real-time gravitational-wave parameter estimation using machine learning

Recorded 17 November 2021. Stephen Green of the Max Planck Institute for Gravitational Physics, Albert Einstein Institute presents "Real-time gravitational-wave parameter estimation using machine learning" at IPAM's Workshop III: Source inference and parameter estimation in Gravitational W

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

Video thumbnail

Replication or Exploration? Sequential Design for Stochastic Simulation Experiments

The Data Science Institute (DSI) hosted a virtual seminar by Robert Gramacy from Virginia Tech on March 15, 2021. Read more about the DSI seminar series at https://data-science.llnl.gov/latest/seminar-series. We investigate the merits of replication and provide methods that search for opti

From playlist DSI Virtual Seminar Series

Video thumbnail

Data Noise | Introduction to Data Mining part 8

In this Data Mining Fundamentals tutorial, we discuss data noise that can overlap valid data and outliers. Noise can appear because of human inconsistency and labeling. We will provide you with several examples of data noise, and how data noise can be measured and recorded. -- Learn more a

From playlist Introduction to Data Mining

Video thumbnail

A high-fidelity, quantum-control-tuned gate set for (...) - H. Bluhm - PRACQSYS 2018 - CEB T2 2018

Hendrik Bluhm (JARA-Institute for Quantum Information, RWTH Aachen University, Aachen, Germany) / 02.07.2018 A high-fidelity, quantum-control-tuned gate set for single-triplet spin qubits Singlet-triplet qubits use the collective spin state of two electrons to encode a single qubit, whic

From playlist 2018 - T2 - Measurement and Control of Quantum Systems: Theory and Experiments

Related pages

Function (mathematics) | Perlin noise | Fractal