Detecting Abrupt Changes by Wavelet Methods

2002 ◽  
Vol 14 (1-2) ◽  
pp. 7-29 ◽  
Author(s):  
Anestis Antoniadis ◽  
Irène Gijbels
Keyword(s):  
Abrupt Changes ◽  
Wavelet Methods

scholarly journals Variations of the Reference Evapotranspiration and Aridity Index Over Northeast China: Changing Properties and Possible Causes

2019 ◽  
Vol 2019 ◽  
pp. 1-13
Author(s):  
Liguo Cao ◽  
Zhengchao Zhou
Keyword(s):  
Northeast China ◽  
Reference Evapotranspiration ◽  
Correlation Coefficients ◽  
Aridity Index ◽  
Kendall Test ◽  
Study Region ◽  
Monsoon Index ◽  
Abrupt Changes ◽  
Temporal And Spatial ◽  
Wavelet Methods

Temporal and spatial variations in reference evapotranspiration (ET0) and aridity index (AI) can be used as important indexes for understanding climate change and its effects on ecosystem stability. Thus, in this work, we comprehensively investigated 71 meteorological stations in Northeast China from 1965 to 2017 to analyze the spatial-temporal variation and trend of ET0 and AI using the nonparametric Mann–Kendall test, the linear regression, and the Morlet wavelet methods. The results elucidated that ET0 for Northeast China as a whole exhibited a decrease at a rate of −1.97 mm/yr, AI declined at a rate of −0.01/yr during 1965–2017, and approximately 94% stations showed a decrease trend. Spatially, the high values of AI and ET0 were primarily at the western part of the study area except for the Heilongjiang province, and the stations showing low values were mainly distributed in the central and eastern part. The decreasing trends for AI were more obvious in the eastern part compared with the western part over the study region. The abrupt changes in AI occurred in 2005 and 2007, whereas only one abrupt change for ET0 occurred in 1995. For annual ET0, there were periods of 3, 7, 11, and 15 yr, and there existed periods of 1, 7, 11, and 13 yr for annual AI. The correlation coefficients implied wind speed and precipitation were the dominant meteorological factors resulting in the ET0 and AI decrease, respectively. Additionally, the change of the Indian summer monsoon index (ISMI) may also contribute to the weakened AI in the study area. Nevertheless, further investigation is still required to clarify the mechanisms for AI and ET0 variations in the future.

Feature Extraction by Best-Basis and Wavelet Methods.

1995 ◽  
Author(s):  
M. V. Wickerhauser ◽  
G. L. Weiss ◽  
R. R. Coifman
Keyword(s):  
Feature Extraction ◽  
Wavelet Methods

scholarly journals Automated Heart Sound Signal Segmentation and Identification using Abrupt Changes and Peak Finding Detection

2021 ◽  
Vol 179 ◽  
pp. 260-267
Author(s):  
Norezmi Jamal ◽  
Nabilah Ibrahim ◽  
MNAH Sha’abani ◽  
Farhanahani Mahmud ◽  
N. Fuad
Keyword(s):  
Heart Sound ◽  
Sound Signal ◽  
Signal Segmentation ◽  
Peak Finding ◽  
Abrupt Changes ◽  
Heart Sound Signal

scholarly journals Model Based Assessment of the Reflection Behavior of Tidal Waves at Bathymetric Changes in Estuaries

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 489
Author(s):  
Vanessa Sohrt ◽  
Sebastian S.V. Hein ◽  
Edgar Nehlsen ◽  
Thomas Strotmann ◽  
Peter Fröhle
Keyword(s):  
Cross Sectional ◽  
High Agreement ◽  
Tidal Waves ◽  
Level Data ◽  
Water Level Data ◽  
Abrupt Changes ◽  
Water Effects ◽  
Potential Impact ◽  
Tidal Constituents ◽  
Harmonic Components

Estuaries are often modified by human activities. Adjustments in the morphology of an estuary have a potential impact on the hydrodynamics and on the reflection behavior of the tide. The influence of such system changes on the complex tidal regime with a large number of superimposed tidal constituents is not fully understood yet. The reflection properties of estuaries that are characterized by abrupt changes in geometry are systematically investigated on the basis of simplified estuary model approaches to improve the understanding of the oscillation and reflection behavior of tidal waves in estuaries. The reflection coefficients at abrupt cross-sectional changes are determined by two different methods, i.e., an analytical energy-based approach and a hydrodynamic numerical (HN) model. Comparisons indicate a high agreement of the results of the different methods when evaluating the reflection coefficient. The tidal constituents are reflected at partial and total reflectors and amplified by shoaling depending on the water depths, the height of the bottom step and the horizontal constriction. A harmonic analysis of simulated water level data partly shows the formation and amplification of higher harmonic components as a result of shallow water effects. The interaction with reflectors results in an increasing amplification of the tidal constituents and the tide.

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