Discrimination of nuclear explosions sites by seismic signals using intrinsic mode functions and multi-modal data space
2008 (English)In: 2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings; Boston, MA; 6 July 2008 through 11 July 2008, 2008, II895-II898 p.Conference paper (Refereed)
Signal processing and feature extraction are investigated using the Empirical Mode Decomposition (EMD). It is believed that this approach is well suited for non-linear and non-stationary data. With EMD any complicated set of data can be decomposed into a finite, and usually small number, of functions called Intrinsic Mode Functions (IMFs). A new discriminating system is presented here that is capable of discriminating between different seismic signals from nuclear testing sites based on the IMFs and the multi-modal data space. The advantage of this space is that multiple metrics of similarity are converted into one single Euclidean space. This space is capable of extracting similarities among several signals through a combination of multiple metrics. This is a new way of associating data. After illustrating the technique with an investigation of an audio data example (piano), we examine the characteristics of seismic signals from nuclear testing (explosions). The results presented in this paper indicate that a relatively simple discriminating system can successfully cluster and classify seismic events.
Place, publisher, year, edition, pages
2008. II895-II898 p.
, International Geoscience and Remote Sensing Symposium (IGARSS), Volume 2, Issue 1, 2008
Hilbert-Huang transform; Intrinsic mode function; Multi-modal data space; Nuclear testing; Seismic data
Engineering and Technology
IdentifiersURN: urn:nbn:se:kth:diva-14103DOI: 10.1109/IGARSS.2008.4779139ScopusID: 2-s2.0-66549094935OAI: oai:DiVA.org:kth-14103DiVA: diva2:329774
QC 201007132010-07-132010-07-132010-07-13Bibliographically approved