Application of the cross wavelet transform and wavelet coherence to geophysical time series

Biostatistical Analysis

Baltosser, W. H., & Zar, J. H. (1996) · Ecology · doi:10.2307/2265725 · Cited by 35,166

The Arctic oscillation signature in the wintertime geopotential height and temperature fields

Thompson, D. W. J., & Wallace, J. M. (1998) · Geophysical Research Letters · doi:10.1029/98gl00950 · Cited by 4,158

The quasi‐biennial oscillation

Baldwin, M., Gray, L. J., Dunkerton, T. J., Hamilton, K., Haynes, P., Randel, W. J., Holton, J. R., Alexander, M. J., Hirota, I., Horinouchi, T., et al. (2001) · Reviews of Geophysics · doi:10.1029/1999rg000073 · Cited by 2,119

Variations of Sea Surface Temperature, Wind Stress, and Rainfall over the Tropical Atlantic and South America

Nobre, P., & Srukla, J. (1996) · Journal of Climate · doi:10.1175/1520-0442(1996)009 · Cited by 893

Influence of the Arctic Oscillation and El Niño‐Southern Oscillation (ENSO) on ice conditions in the Baltic Sea: The wavelet approach

Jevrejeva, S., Moore, J. C., & Grinsted, A. (2003) · Journal of Geophysical Research Atmospheres · doi:10.1029/2003jd003417 · Cited by 427

Wavelets in Geophysics

(1994) · Wavelet analysis and its applications · doi:10.1016/c2009-0-21241-4 · Cited by 376

Influence of atmospheric circulation on the maximum ice extent in the Baltic Sea

Omstedt, A., & Chen, D. (2001) · Journal of Geophysical Research Atmospheres · doi:10.1029/1999jc000173 · Cited by 139

Singular spectrum analysis of Baltic Sea ice conditions and large‐scale atmospheric patterns since 1708

Jevrejeva, S., & Moore, J. C. (2001) · Geophysical Research Letters · doi:10.1029/2001gl013573 · Cited by 55

The Western Baltic sea ice season in terms of a mass-related severity index 1879–1992: (II). Spectral characteristics and associations with the NAO, QBO, and solar cycle

Loewe, P., & Koslowski, G. (1998) · Tellus A Dynamic Meteorology and Oceanography · doi:10.3402/tellusa.v50i2.14522 · Cited by 28

The Western Baltic sea ice season in terms of a mass-related severity index 1879-1992. (II). Spectral characteristics and associations with the NAO, QBO and solar cycle

Loewe, P., & Koslowski, G. (1998) · Tellus A Dynamic Meteorology and Oceanography · doi:10.1034/j.1600-0870.1998.t01-1-00005.x · Cited by 21

Time-lagged response of vegetation dynamics to climatic and teleconnection factors

Zhao, J., Huang, S., Huang, Q., Wang, H. E., Leng, G., & Fang, W. (2020) · CATENA · doi:10.1016/j.catena.2020.104474 · Cited by 184

Temporal Dynamics in Soil Oxygen and Greenhouse Gases in Two Humid Tropical Forests

Liptzin, D., Silver, W. L., & Detto, M. (2010) · Ecosystems · doi:10.1007/s10021-010-9402-x · Cited by 184

The interaction of ultra-low-frequency pc3-5 waves with charged particles in Earth’s magnetosphere

Zong, Q., Rankin, R., & Zhou, X. (2017) · Reviews of Modern Plasma Physics · doi:10.1007/s41614-017-0011-4 · Cited by 179

Using wavelet tools to analyse seasonal variations from InSAR time-series data: a case study of the Huangtupo landslide

Tomás, R., Li, Z., Lopez-Sanchez, J. M., Liu, P., & Singleton, A. (2015) · Landslides · doi:10.1007/s10346-015-0589-y · Cited by 178

Co-movement of Asia-Pacific with European and US stock market returns: A cross-time-frequency analysis

Loh, L. (2013) · Research in International Business and Finance · doi:10.1016/j.ribaf.2013.01.001 · Cited by 178

Solar activity during the Holocene: the Hallstatt cycle and its consequence for grand minima and maxima

Usoskin, I. G., Gallet, Y., Lopes, F., Kovaltsov, G. A., & Hulot, G. (2016) · Astronomy & Astrophysics · doi:10.1051/0004-6361/201527295 · Cited by 176

Species fluctuations sustained by a cyclic succession at the edge of chaos

Benincà, E., Ballantine, B., Ellner, S. P., & Huisman, J. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1421968112 · Cited by 171

Ground surface response to continuous compaction of aquifer system in Tehran, Iran: Results from a long-term multi-sensor InSAR analysis

Haghighi, M. H., & Motagh, M. (2018) · Remote Sensing of Environment · doi:10.1016/j.rse.2018.11.003 · Cited by 176

Inter-brain synchrony in mother-child dyads during cooperation: An fNIRS hyperscanning study

Miller, J. G., Vrtička, P., Cui, X., Shrestha, S. B., Hosseini, S. M. H., Baker, J. M., & Reiss, A. L. (2018) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2018.12.021 · Cited by 181

North American monsoon precipitation reconstructed from tree‐ring latewood

Griffin, D., Woodhouse, C. A., Meko, D. M., Stahle, D. W., Faulstich, H. L., Carrillo, C. M., Touchan, R., Castro, C. L., & Leavitt, S. W. (2013) · Geophysical Research Letters · doi:10.1002/grl.50184 · Cited by 174

Region-wide synchrony and traveling waves of dengue across eight countries in Southeast Asia

van Panhuis, W. G., Choisy, M., Xiong, X., Chok, N. S., Akarasewi, P., Iamsirithaworn, S., Lam, S. K., Chong, C. K., Lam, F. C., Phommasack, B., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1501375112 · Cited by 173

Neural mechanisms for selectively tuning in to the target speaker in a naturalistic noisy situation

Dai, B., Chen, C., Long, Y., Zheng, L., Zhao, H., Bai, X., Liu, W., Zhang, Y., Liu, L., Guo, T., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-04819-z · Cited by 172

Quantitative contribution of climate change and human activities to vegetation cover variations based on GA-SVM model

Huang, S., Zheng, X., Ma, L., Wang, H. E., Huang, Q., Leng, G., Meng, E., & Guo, Y. (2020) · Journal of Hydrology · doi:10.1016/j.jhydrol.2020.124687 · Cited by 172

Biophysical controls on interannual variability in ecosystem‐scale CO 2 and CH 4 exchange in a California rice paddy

Knox, S., Matthes, J. H., Sturtevant, C., Oikawa, P. Y., Verfaillie, J., & Baldocchi, D. (2016) · Journal of Geophysical Research Biogeosciences · doi:10.1002/2015jg003247 · Cited by 171

Interpersonal Neural Entrainment during Early Social Interaction

Wass, S. V., Whitehorn, M., Haresign, I. M., Phillips, E., & Leong, V. (2020) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2020.01.006 · Cited by 175

Using Fiberless, Wearable fNIRS to Monitor Brain Activity in Real-world Cognitive Tasks

Pinti, P., Aichelburg, C., Lind, F., Power, S., Swingler, E., Merla, A., Hamilton, A., Gilbert, S., Burgess, P., & Tachtsidis, I. (2015) · Journal of Visualized Experiments · doi:10.3791/53336 · Cited by 169

A time-frequency analysis of trade openness and CO2 emissions in France

Mutascu, M. I. (2018) · Energy Policy · doi:10.1016/j.enpol.2018.01.034 · Cited by 169

Effects of the COVID-19 pandemic on the US stock market and uncertainty: A comparative assessment between the first and second waves

Yousfi, M., Zaied, Y. B., Cheikh, N. B., Lahouel, B. B., & Bouzgarrou, H. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.120710 · Cited by 169

Cross-Wavelet Bias Corrected by Normalizing Scales

Veleda, D., Montagne, R., & Araújo, M. (2012) · Journal of Atmospheric and Oceanic Technology · doi:10.1175/jtech-d-11-00140.1 · Cited by 168

Evolution of vegetation and climate variability on the Tibetan Plateau over the past 1.74 million years

Zhao, Y., Tzedakis, P. C., Li, Q., Qin, F., Cui, Q., Chen, L., Birks, H. J. B., Liu, Y., Zhang, Z., Ge, J., et al. (2020) · Science Advances · doi:10.1126/sciadv.aay6193 · Cited by 168

Dynamic coherence analysis of resting fMRI data to jointly capture state-based phase, frequency, and time-domain information

Yaesoubi, M., Allen, E. A., Miller, R. L., & Calhoun, V. D. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.07.002 · Cited by 168

Inter‐subject synchronization of brain responses during natural music listening

Abrams, D. A., Ryali, S., Chen, T., Chordia, P., Khouzam, A., Levitin, D. J., & Menon, V. (2013) · European Journal of Neuroscience · doi:10.1111/ejn.12173 · Cited by 167

A deep learning approach to monitoring and detecting atrial fibrillation using wearable technology

Shashikumar, S. P., Shah, A. J., Qiao, L., Clifford, G. D., & Nemati, S. (2017) · IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...) · doi:10.1109/bhi.2017.7897225 · Cited by 167

Multiscale analysis of temporal variability of soil CO2 production as influenced by weather and vegetation

Vargas, R., Detto, M., Baldocchi, D., & Allen, M. F. (2009) · Global Change Biology · doi:10.1111/j.1365-2486.2009.02111.x · Cited by 166

Neural synchrony in mother-child conversation: Exploring the role of conversation patterns

Nguyen, T., Schleihauf, H., Kayhan, E., Matthes, D., Vrtička, P., & Hoehl, S. (2021) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsaa079 · Cited by 165

Reorganization of functional connectivity as a correlate of cognitive recovery in acquired brain injury

Castellanos, N. P., Paúl, N., Ordóñez, V. E., Demuynck, O., Bajo, R., Campo, P., Bilbao, Á., Ortiz, T., del Pozo, F., & Maestú, F. (2010) · Brain · doi:10.1093/brain/awq174 · Cited by 166

How Two Brains Make One Synchronized Mind in the Inferior Frontal Cortex: fNIRS-Based Hyperscanning During Cooperative Singing

Osaka, N., Minamoto, T., Yaoi, K., Azuma, M., Shimada, Y. M., & Osaka, M. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.01811 · Cited by 166

River flow controls on tides and tide‐mean water level profiles in a tidal freshwater river

Sassi, M. G., & Hoitink, A. J. F. (2013) · Journal of Geophysical Research Oceans · doi:10.1002/jgrc.20297 · Cited by 163

Wavelet analysis of hydrological and water quality signals in an agricultural watershed

Kang, S. K., & Lin, H. (2007) · Journal of Hydrology · doi:10.1016/j.jhydrol.2007.01.047 · Cited by 162

A novel approach to the detection of synchronisation in EEG based on empirical mode decomposition

Sweeney‐Reed, C. M., & Nasuto, S. J. (2007) · Journal of Computational Neuroscience · doi:10.1007/s10827-007-0020-3 · Cited by 163

Molecular records of continental air temperature and monsoon precipitation variability in East Asia spanning the past 130,000 years

Peterse, F., Martínez‐García, A., Zhou, B., Beets, C. J., Prins, M. A., Zheng, H., & Eglinton, T. I. (2013) · Quaternary Science Reviews · doi:10.1016/j.quascirev.2013.11.001 · Cited by 161

Frontiers and challenges in soil respiration research: from measurements to model-data integration

Vargas, R., Carbone, M. S., Reichstein, M., & Baldocchi, D. (2010) · Biogeochemistry · doi:10.1007/s10533-010-9462-1 · Cited by 163

Analyzing time–frequency co-movements across gold and oil prices with BRICS stock markets: A VaR based on wavelet approach

Mensi, W., Hkiri, B., Al‐Yahyaee, K. H., & Kang, S. H. (2017) · International Review of Economics & Finance · doi:10.1016/j.iref.2017.07.032 · Cited by 161

High resolution monsoon precipitation changes on southeastern Tibetan Plateau over the past 2300 years

Tan, L., Cai, Y., Cheng, H., Edwards, L. R., Lan, J., Zhang, H., Li, D., Ma, L., Zhao, P., & Gao, Y. (2018) · Quaternary Science Reviews · doi:10.1016/j.quascirev.2018.07.021 · Cited by 161

A history of solar activity over millennia

USOSKIN, I. G. (2023) · Living Reviews in Solar Physics · doi:10.1007/s41116-023-00036-z · Cited by 187

International stock market indices comovements: a new look

Madaleno, M., & Pinho, C. (2011) · International Journal of Finance & Economics · doi:10.1002/ijfe.448 · Cited by 160

Spatial and temporal distribution of rainfall and drought characteristics across the Pearl River basin

Deng, S., Chen, T., Yang, N., Qu, L., Li, M., & Chen, D. (2017) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2017.10.339 · Cited by 158

The influence of biomass energy consumption on CO2 emissions: a wavelet coherence approach

Bilgili, F., Öztürk, İ., Koçak, E., Bulut, Ü., Pamuk, Y., Muğaloğlu, E., & Bağlıtaş, H. H. (2016) · Environmental Science and Pollution Research · doi:10.1007/s11356-016-7094-2 · Cited by 155

The short-term effects of air pollutants on influenza-like illness in Jinan, China

Su, W., Wu, X., Geng, X., Zhao, X., Liu, Q., & Liu, T. (2019) · BMC Public Health · doi:10.1186/s12889-019-7607-2 · Cited by 157

Foehn winds link climate‐driven warming to ice shelf evolution in Antarctica

Cape, M., Vernet, M., Skvarca, P., Marinsek, S., Scambos, T. A., & Domack, E. W. (2015) · Journal of Geophysical Research Atmospheres · doi:10.1002/2015jd023465 · Cited by 156

The geography of spatial synchrony

Walter, J. A., Sheppard, L. W., Anderson, T. L., Kastens, J. H., Bjørnstad, O. N., Liebhold, A. M., & Reuman, D. C. (2017) · Ecology Letters · doi:10.1111/ele.12782 · Cited by 156

High-resolution Holocene South American monsoon history recorded by a speleothem from Botuverá Cave, Brazil

Bernal, J. P., Cruz, F. W., Stríkis, N. M., Wang, X., Deininger, M., Catunda, M. C. A., Ortega‐Obregón, C., Cheng, H., Edwards, R. L., & Auler, A. S. (2016) · Earth and Planetary Science Letters · doi:10.1016/j.epsl.2016.06.008 · Cited by 163

Real-life creative problem solving in teams: fNIRS based hyperscanning study

Mayseless, N., Hawthorne, G., & Reiss, A. L. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116161 · Cited by 155

Spatial and temporal variability of precipitation over China, 1951–2005

Zhang, Q., Xu, C., Zhang, Z., Chen, Y., & Liu, C.-L. (2008) · Theoretical and Applied Climatology · doi:10.1007/s00704-007-0375-4 · Cited by 154

Is there a planetary influence on solar activity?

Abreu, J. A., Beer, J., Ferriz-Mas, A., McCracken, K. G., & Steinhilber, F. (2012) · Astronomy and Astrophysics · doi:10.1051/0004-6361/201219997 · Cited by 154

Interannual sea level variability in the South China Sea and its response to ENSO

Rong, Z., Liu, Y., Zong, H., & Cheng, Y. (2006) · Global and Planetary Change · doi:10.1016/j.gloplacha.2006.08.001 · Cited by 154

Groundwater level response in U.S. principal aquifers to ENSO, NAO, PDO, and AMO

Kuss, A. J., & Gurdak, J. J. (2014) · Journal of Hydrology · doi:10.1016/j.jhydrol.2014.09.069 · Cited by 153

Interdecadal variability of the relationship between the East Asian winter monsoon and ENSO

Zhou, W., Wang, X., Zhou, T., Li, C., & Chan, J. C. L. (2007) · Meteorology and Atmospheric Physics · doi:10.1007/s00703-007-0263-6 · Cited by 152

Automatic noise-removal/signal-removal based on general cross-validation thresholding in synchrosqueezed domain and its application on earthquake data

Mousavi, S. M., & Langston, C. A. (2017) · Geophysics · doi:10.1190/geo2016-0433.1 · Cited by 151

Onset and Evolution of Southern Annular Mode-Like Changes at Centennial Timescale

Moreno, P. I., Vilanova, I., Villa-Martínez, R. P., Dunbar, R. B., Mucciarone, D. A., Kaplan, M. R., Garreaud, R. D., Rojas, M., Moy, C. M., Pol-Holz, R. H. D., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-21836-6 · Cited by 151

A European pattern climatology 1766–2000

Casty, C., Raible, C. C., Stocker, T. F., Wanner, H., & Luterbacher, J. (2007) · Climate Dynamics · doi:10.1007/s00382-007-0257-6 · Cited by 150

Biosphere-atmosphere exchange of CO 2 in relation to climate: a cross-biome analysis across multiple time scales

Stoy, P. C., Richardson, A. D., Baldocchi, D., Katul, G. G., Stanovick, J. S., Mahecha, M. D., Reichstein, M., Detto, M., Law, B. E., Wohlfahrt, G., et al. (2009) · Biogeosciences · doi:10.5194/bg-6-2297-2009 · Cited by 151

Spatial distribution, temporal variation, and transport characteristics of atmospheric water vapor over Central Asia and the arid region of China

Guan, X., Yang, L., Zhang, Y., & Li, J. (2018) · Global and Planetary Change · doi:10.1016/j.gloplacha.2018.06.007 · Cited by 150

Large‐scale climatic patterns control large lightning fire occurrence in Canada and Alaska forest regions

Macias‐Fauria, M., & Johnson, E. A. (2006) · Journal of Geophysical Research Atmospheres · doi:10.1029/2006jg000181 · Cited by 149

Propagation characteristics and mechanism from meteorological to agricultural drought in various seasons

Dai, M., Huang, S., Huang, Q., Zheng, X., Su, X., Leng, G., Li, Z., Guo, Y., Fang, W., & Liu, Y. (2022) · Journal of Hydrology · doi:10.1016/j.jhydrol.2022.127897 · Cited by 149

Impact of changes in barometric pressure on landfill methane emission

Xu, L., Lin, X., Amen, J., Welding, K., & McDermitt, D. K. (2014) · Global Biogeochemical Cycles · doi:10.1002/2013gb004571 · Cited by 148

Southern Ocean upwelling, Earth’s obliquity, and glacial-interglacial atmospheric CO 2 change

Ai, X. E., Studer, A. S., Sigman, D. M., Martínez‐García, A., Fripiat, F., Thöle, L. M., Michel, É., Gottschalk, J., Arnold, L., Moretti, S., et al. (2020) · Science · doi:10.1126/science.abd2115 · Cited by 148

Integration of 22 emerging stock markets: A three-dimensional analysis

Graham, M., Kiviaho, J., & Nikkinen, J. (2012) · Global Finance Journal · doi:10.1016/j.gfj.2012.01.003 · Cited by 147

Cryptocurrency price drivers: Wavelet coherence analysis revisited

Phillips, R. C., & Gorse, D. (2018) · PLoS ONE · doi:10.1371/journal.pone.0195200 · Cited by 147

A review of resource curse burden on inflation in Venezuela

Su, C., Khan, K. B., Tao, R., & Umar, M. (2020) · Energy · doi:10.1016/j.energy.2020.117925 · Cited by 147

Landslide displacement prediction based on variational mode decomposition and WA-GWO-BP model

Guo, Z., Chen, L., Gui, L., Du, J., Yin, K., & Do, H. M. (2019) · Landslides · doi:10.1007/s10346-019-01314-4 · Cited by 147

Recurrence of bloom-forming scyphomedusae: wavelet analysis of a 200-year time series

Kogovšek, T., Bogunović, B., & Malej, A. (2010) · Hydrobiologia · doi:10.1007/s10750-010-0217-8 · Cited by 146

Wavelet analysis in neurodynamics

Pavlov, A. N., Hramov, A. E., Koronovskii, A. A., Sitnikova, E., Makarov, V. A., & Ovchinnikov, A. A. (2012) · Physics-Uspekhi · doi:10.3367/ufne.0182.201209a.0905 · Cited by 146

On the multi‐temporal correlation between photosynthesis and soil CO2 efflux: reconciling lags and observations

Vargas, R., Baldocchi, D., Bahn, M., Hanson, P. J., Hosman, K. P., Kulmala, L., Pumpanen, J., & Yang, B. (2011) · New Phytologist · doi:10.1111/j.1469-8137.2011.03771.x · Cited by 145

Sea level monitoring and sea state estimate using a single geodetic receiver

Roussel, N., Ramillien, G., Frappart, F., Darrozes, J., Gay, A., Biancale, R., Striebig, N., Hanquiez, V., Bertin, X., & Allain, D. J. (2015) · Remote Sensing of Environment · doi:10.1016/j.rse.2015.10.011 · Cited by 145

Cooperation Makes a Group be More Creative

Lu, K., Xue, H., Nozawa, T., & Hao, N. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy215 · Cited by 147

Gross ecosystem photosynthesis causes a diurnal pattern in methane emission from rice

Matthes, J. H., Detto, M., & Baldocchi, D. (2012) · Geophysical Research Letters · doi:10.1029/2012gl051303 · Cited by 144

Hydroclimate variability of the northwestern Amazon Basin near the Andean foothills of Peru related to the South American Monsoon System during the last 1600 years

Apaéstegui, J., Cruz, F. W., Sifeddine, A., Vuille, M., Espinoza, J. C., Guyot, J., Khodri, M., Stríkis, N. M., Santos, R. V., Cheng, H., et al. (2014) · Climate of the past · doi:10.5194/cp-10-1967-2014 · Cited by 144

Crises and contagion in Asia Pacific — Islamic v/s conventional markets

Rizvi, S. A. R., Arshad, S., & Alam, N. (2015) · Pacific-Basin Finance Journal · doi:10.1016/j.pacfin.2015.04.002 · Cited by 144

Cyclostratigraphic constraints on the duration of the Datangpo Formation and the onset age of the Nantuo (Marinoan) glaciation in South China

Bao, X., Zhang, S., Jiang, G., Wu, H., Li, H., Wang, X., An, Z., & Yang, T. (2017) · Earth and Planetary Science Letters · doi:10.1016/j.epsl.2017.12.001 · Cited by 143

The relationship between Bitcoin returns and trade policy uncertainty

Gözgör, G., Tiwari, A. K., Demir, E., & Akron, S. (2019) · Finance research letters · doi:10.1016/j.frl.2019.03.016 · Cited by 143

Linkages between hydrological drought, climate indices and human activities: a case study in the Columbia River basin

Huang, S., Huang, Q., Chang, J., & Leng, G. (2015) · International Journal of Climatology · doi:10.1002/joc.4344 · Cited by 142

Improvisation and the self-organization of multiple musical bodies

Walton, A. E., Richardson, M. J., Langland‐Hassan, P., & Chemero, A. P. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00313 · Cited by 150

Roughness Encoding for Discrimination of Surfaces in Artificial Active-Touch

Oddo, C. M., Controzzi, M., Beccai, L., Cipriani, C., & Carrozza, M. C. (2011) · IEEE Transactions on Robotics · doi:10.1109/tro.2011.2116930 · Cited by 143

Analysis of pattern–process interactions based on landscape models—Overview, general concepts, and methodological issues

Schröder, B., & Seppelt, R. (2006) · Ecological Modelling · doi:10.1016/j.ecolmodel.2006.05.036 · Cited by 141

Anticorrelated resting-state functional connectivity in awake rat brain

Liang, Z., King, J. A., & Zhang, N. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.08.009 · Cited by 139

Characterization of Dynamic Interactions Between Cardiovascular Signals by Time-Frequency Coherence

Orini, M., Bailón, R., Mainardi, L. T., Laguna, P., & Flandrin, P. (2011) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2011.2171959 · Cited by 140

Cooperative Behavior Evokes Interbrain Synchrony in the Prefrontal and Temporoparietal Cortex: A Systematic Review and Meta-Analysis of fNIRS Hyperscanning Studies

Czeszumski, A., Liang, S. H., Dikker, S., Peter König, B., Lee, C., Koole, S. L., & Kelsen, B. A. (2022) · eNeuro · doi:10.1523/eneuro.0268-21.2022 · Cited by 153

The continuous wavelet transform : a primer

Aguiar‐Conraria, L., & Soares, M. J. (2011) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · Cited by 137

Altered Activity in the Central Medial Thalamus Precedes Changes in the Neocortex during Transitions into Both Sleep and Propofol Anesthesia

Baker, R. H., Gent, T. C., Yang, Q., Parker, S., Vyssotski, A. L., Wisden, W., Brickley, S. G., & Franks, N. P. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.1519-14.2014 · Cited by 149

Precipitation changes in the South American Altiplano since 1300 AD reconstructed by tree-rings

Morales, M. S., Christie, D. A., Villalba, R., Argollo, J., Pacajes, J., Silva, J. S., Alvarez, C. A., Llancabure, J. C., & Soliz Gamboa, C. C. (2012) · Climate of the Past · doi:10.5194/cp-8-653-2012 · Cited by 112

On the event-based extreme precipitation across China: Time distribution patterns, trends, and return levels

Wu, X., Guo, S., Yin, J., Yang, G., Zhong, Y., & Liu, D. (2018) · Journal of Hydrology · doi:10.1016/j.jhydrol.2018.05.028 · Cited by 138

A tale of company fundamentals vs sentiment driven pricing: The case of GameStop

Umar, Z., Gubareva, M., Yousaf, I., & Ali, S. (2021) · Journal of Behavioral and Experimental Finance · doi:10.1016/j.jbef.2021.100501 · Cited by 135

A Survey on Change Detection and Time Series Analysis with Applications

Ghaderpour, E., Pagiatakis, S. D., & Hassan, Q. K. (2021) · Applied Sciences · doi:10.3390/app11136141 · Cited by 137

Planetary waves in coupling the stratosphere and mesosphere during the major stratospheric warming in 2003/2004

Pancheva, D. V., Mukhtarov, P. Y., Mitchell, N. J., Merzlyakov, E. G., Smith, A. K., Andonov, B., Singer, W., Hocking, W. K., Meek, C. E., Manson, A. H., et al. (2008) · Journal of Geophysical Research Atmospheres · doi:10.1029/2007jd009011 · Cited by 137

Wavelet Coherence Model for Diagnosis of Alzheimer Disease

Sankari, Z., Adeli, H., & Adeli, A. (2012) · Clinical EEG and Neuroscience · doi:10.1177/1550059412444970 · Cited by 137

Co-movement of oil and stock prices in the GCC region: A wavelet analysis

Akoum, I. F., Graham, M., Kivihaho, J., Nikkinen, J., & Omran, M. (2012) · The Quarterly Review of Economics and Finance · doi:10.1016/j.qref.2012.07.005 · Cited by 136

Identifying and quantifying main components of physiological noise in functional near infrared spectroscopy on the prefrontal cortex

Kirlilna, E., Yu, N. H., Jelzow, A., Wabnitz, H., Jacobs, A. M., & Tachtsidis, I. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00864 · Cited by 138

Acute effects of air pollution on influenza-like illness in Nanjing, China: A population-based study

Huang, L., Zhou, L., Chen, J., Chen, K., Liu, Y., Chen, X., & Tang, F. (2016) · Chemosphere · doi:10.1016/j.chemosphere.2015.12.082 · Cited by 136

Mode transitions in Northern Hemisphere glaciation: co-evolution of millennial and orbital variability in Quaternary climate

Hodell, D. A., & Channell, J. E. T. (2016) · Climate of the past · doi:10.5194/cp-12-1805-2016 · Cited by 136

Impact of COVID-19 pandemic on stock markets: Conventional vs. Islamic indices using wavelet-based multi-timescales analysis

Hasan, M. B., Mahi, M., Hassan, M. K., & Bhuiyan, A. B. (2021) · The North American Journal of Economics and Finance · doi:10.1016/j.najef.2021.101504 · Cited by 136

Spatial Scaling Analyses of Soil Physical Properties: A Review of Spectral and Wavelet Methods

Si, B. (2008) · Vadose Zone Journal · doi:10.2136/vzj2007.0040 · Cited by 136

PM2.5 in Beijing – temporal pattern and its association with influenza

Liang, Y., Fang, L., Pan, H., Zhang, K., Kan, H., Brook, J. R., & Sun, Q. (2014) · Environmental Health · doi:10.1186/1476-069x-13-102 · Cited by 135

Analysis of space–time non-stationary patterns of rainfall–groundwater interactions by integrating empirical orthogonal function and cross wavelet transform methods

Yu, H., & Lin, Y. (2015) · Journal of Hydrology · doi:10.1016/j.jhydrol.2015.03.057 · Cited by 135

Monitoring Pilot's Cognitive Fatigue with Engagement Features in Simulated and Actual Flight Conditions Using an Hybrid fNIRS-EEG Passive BCI

Dehais, F., Duprès, A., Flumeri, G. D., Verdière, K. J., Borghini, G., Babiloni, F., & Roy, R. N. (2018) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2018.00102 · Cited by 144

Precipitation variability and fire influence the temporal dynamics of soil CO 2 efflux in an arid grassland

Vargas, R., Collins, S. L., Thomey, M. L., Johnson, J. E., Brown, R. F., Natvig, D. O., & Friggens, M. T. (2011) · Global Change Biology · doi:10.1111/j.1365-2486.2011.02628.x · Cited by 133

Spatial and wavelet analysis of precipitation and river discharge during operation of the Three Gorges Dam, China

Yin, L., Wang, L., Keim, B. D., Konsoer, K., Yin, Z., Liu, M., & Zheng, W. (2023) · Ecological Indicators · doi:10.1016/j.ecolind.2023.110837 · Cited by 134

Transferable wavelet method for grain‐size distribution from images of sediment surfaces and thin sections, and other natural granular patterns

Buscombe, D. (2013) · Sedimentology · doi:10.1111/sed.12049 · Cited by 133

Rethinking Measures of Functional Connectivity via Feature Extraction

Mohanty, R., Sethares, W. A., Nair, V. A., & Prabhakaran, V. (2020) · Scientific Reports · doi:10.1038/s41598-020-57915-w · Cited by 145

Cross wavelet analysis: significance testing and pitfalls

Maraun, D., & Kurths, J. (2004) · Nonlinear processes in geophysics · doi:10.5194/npg-11-505-2004 · Cited by 576

Nonlinear Processes in Geophysics

Maraun, D., & Kurths, J. (2013)

Significance and Causality in Continuous Wavelet and Wavelet Coherence Spectra Applied to Hydrological Time Series

Rodríguez-Murillo, J. C., & Filella, M. (2020) · Hydrology · doi:10.3390/hydrology7040082 · Cited by 30

Wavelet coherence analysis for GPS time series

Guo-qing, Q., & Su, X. (2010) · Meitan xuebao · Cited by 1

Significance tests for the wavelet cross spectrum and wavelet linear coherence

Ge, Z. (2008) · Annales Geophysicae · doi:10.5194/angeo-26-3819-2008 · Cited by 77