000 04434nam a22005175i 4500
001 978-3-642-16449-1
003 DE-He213
005 20140220083749.0
007 cr nn 008mamaa
008 110812s2011 gw | s |||| 0|eng d
020 _a9783642164491
_9978-3-642-16449-1
024 7 _a10.1007/978-3-642-16449-1
_2doi
050 4 _aGB5000-5030
072 7 _aRNR
_2bicssc
072 7 _aNAT023000
_2bisacsh
082 0 4 _a551
_223
100 1 _aVarotsos, Panayiotis A.
_eauthor.
245 1 0 _aNatural Time Analysis: The New View of Time
_h[electronic resource] :
_bPrecursory Seismic Electric Signals, Earthquakes and other Complex Time Series /
_cby Panayiotis A. Varotsos, Nicholas V. Sarlis, Efthimios S. Skordas.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2011.
300 _aXXIV, 452 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Praxis Books
505 0 _aPart I Seismic Electric Signals -- 1. Introduction to Seismic Electric Signals-V -- Part II -- 2. Natural Time. Background-F -- 3. Entropy in Natural Time-E -- Part III Natural Time Applications -- 4. Natural Time Analysis of Seismic Electric Signals-AS -- 5. Natural Time Investigation of the Effect of Significant Data Loss on Indentifying Seismic Electric Signals-ASL -- 6. Natural Time Analysis of Seismicity-AEQ -- 7. Indentifying the Occurence Time of an Impending Mainshock-AIM -- 8. Natural Time Analysis of Dynamical Models-AD -- 9. Natural Time Analysis of Electrocardiograms-AEL -- References.
520 _aThis book deals with the theory and the applications of a new time domain, termed natural time domain, that has been forwarded by the authors almost a decade ago (P.A. Varotsos, N.V. Sarlis and E.S. Skordas, Practica of Athens Academy 76, 294-321, 2001; Physical Review E 66, 011902, 2002). In particular, it has been found that novel dynamical features hidden behind time series in complex systems can emerge upon analyzing them in this new time domain, which conforms to the desire to reduce uncertainty and extract signal information as much as possible. The analysis in natural time enables the study of the dynamical evolution of a complex system and identifies when the system enters a critical stage. Hence, natural time plays a key role in predicting impending catastrophic events in general. Relevant examples of data analysis in this new time domain have been published during the last decade in a large variety of fields, e.g., Earth Sciences, Biology and Physics. The book explains in detail a series of such examples including the identification of the sudden cardiac death risk in Cardiology, the recognition of electric signals that precede earthquakes, the determination of the time of an impending major mainshock in Seismology, and the analysis of the avalanches of the penetration of magnetic flux into thin films of type II superconductors in Condensed Matter Physics. In general, this book is concerned with the time-series analysis of signals emitted from complex systems by means of the new time domain and provides advanced students and research workers in diverse fields with a sound grounding in the fundamentals of current research work on detecting (long-range) correlations in complex time series. Furthermore, the modern techniques of Statistical Physics in time series analysis, for example Hurst analysis, the detrended fluctuation analysis, the wavelet transform etc., are presented along with their advantages when natural time domain is employed.
650 0 _aGeography.
650 0 _aGeology.
650 1 4 _aEarth Sciences.
650 2 4 _aNatural Hazards.
650 2 4 _aStatistical Physics, Dynamical Systems and Complexity.
650 2 4 _aEarth Sciences, general.
650 2 4 _aBiophysics and Biological Physics.
650 2 4 _aGeophysics and Environmental Physics.
650 2 4 _aCondensed Matter Physics.
700 1 _aSarlis, Nicholas V.
_eauthor.
700 1 _aSkordas, Efthimios S.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642164484
830 0 _aSpringer Praxis Books
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-16449-1
912 _aZDB-2-EES
999 _c107153
_d107153