Cart (Loading....) | Create Account
Close category search window

Distinguishing signal from noise in an SVD of simulation data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Constantine, P.G. ; Mech. Eng. Dept., Stanford Univ., Stanford, CA, USA ; Gleich, D.F.

Our goal is to predict the output of a parameterized computer simulation code given a database of outputs at different parameter values. To do so, we investigate a particular model reduction technique that interpolates the right singular vectors in the singular value decomposition of the matrix of outputs. A common observation about these singular vectors is that they become more oscillatory as the index of the singular vectors increases. We use this property to split the singular vectors into “signal” and “noise” regions. The model reduction then interpolates the “signal” and uses the “noise” to estimate the uncertainty in the result. This methodology requires a big-data approach because the simulations we study produce snapshots with hundreds or thousands of timesteps on thousands to millions of nodal values. Each simulation output is then a vector with millions to billions of values. We utilize a MapReduce-based SVD routine to compute the SVD of the snapshot matrix.

Published in:

Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on

Date of Conference:

25-30 March 2012

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.