CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
Seismic pattern recognition by Wavelet based-higher order statistics
Authors
Kharintsev S.
Salakhov M.
Publication date
1 January 2005
Publisher
Abstract
In this work we develop an approach for detecting nonlinearity in chaotic dynamical systems using the higher order statistics and wavelet analysis. A special attention is paid to the consideration of three-wave interaction in a quadratically coupled medium. The knowledge of nonlinearities allows one to extract order parameters both for reconstruction of a dynamical system and for the study of transient processes between oscillatory regimes. To demonstrate a power of this approach we verify the latter for real data coming from the seismology. © 2005 American Institute of Physics
Similar works
Full text
Open in the Core reader
Download PDF
Available Versions
Kazan Federal University Digital Repository
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:dspace.kpfu.ru:net/135234
Last time updated on 07/05/2019