Spectral and wavelet methods for the analysis of nonlinear and nonstationary time series

Rao, T. Subba; Indukumar, K.C.

doi:10.1016/0016-0032(96)00011-7

Cited by 17 publications

(4 citation statements)

References 17 publications

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“…In addition, to identify the abnormal time periods for meteorological conditions, wavelet analysis was used in this study to describe the fluctuation and attenuation characteristics and mark the abnormal time period. Specifically, we used the continuous wavelet transform (CWT) method [46,47], and the formula of this method is as follows:…”

Section: Meteorological Data Analysismentioning

confidence: 99%

Exploring the Influence Mechanism of Meteorological Conditions on the Concentration of Suspended Solids and Chlorophyll-a in Large Estuaries Based on MODIS Imagery

Yao

et al. 2019

Water

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In estuary areas, meteorological conditions have become unstable under the continuous effects of climate change, and the ecological backgrounds of such areas have strongly been influenced by anthropic activities. Consequently, the water quality of these areas is obviously affected. In this research, we identified periods of fluctuation of the general meteorological conditions in the Yangtze River Estuary using a wavelet analysis. Additionally, we performed a spatiotemporal evaluation of the water quality in the fluctuating period by using remote sensing modeling. Then, we explored how the fluctuating meteorological factors affect the distribution of total suspended solids (TSS) and chlorophyll-a (Chla) concentration. (1) The results show that from 2000 to 2015, temperature did not present significant fluctuations, while wind speed (WS) and precipitation (PR) presented the same fluctuation period from January 2012 to December 2012. (2) Based on the measured water sample data associated with Moderate Resolution Imaging Spectroradiometer (MODIS) imagery, we developed a water quality algorithm and depicted the TSS and Chla concentrations within the WS and PR fluctuating period. (3) We found that the TSS concentration decreased with distance from the shore, while the Chla concentration showed an initially decreasing trend followed by an increasing trend; moreover, these two water quality parameters presented different inter-annual variations. Then, we discussed the correlation between the changes in the TSS and Chla concentrations and the WS and PR variables. The contribution of this research is reflected in two aspects: 1. variations in water quality parameters over a wide range of water bodies can be evaluated based on MODIS data; 2. data from different time periods showed that the fluctuations of meteorological elements had different impacts on water bodies based on the distance from the shore. The results provide new insights for the management of estuary water environments.

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Section: Meteorological Data Analysismentioning

confidence: 99%

Exploring the Influence Mechanism of Meteorological Conditions on the Concentration of Suspended Solids and Chlorophyll-a in Large Estuaries Based on MODIS Imagery

Yao

et al. 2019

Water

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“…This paper also suggests future lines of research to establish relationships between and usage of our practical method with other research and methods in statistics and engineering, such as methods with strong engineering roots for forecasting/predicting the behavior of economic variables, which found a wide application base in business and economics [10,11], and methods that are commonly used in both social science and physics such the Bayesian approach [12] and transfer function [13].…”

Section: Introductionmentioning

confidence: 98%

A confidence interval test for the detection of structural breaks

Genç

Arzaghi

2011

Journal of the Franklin Institute

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“…Nevertheless, its properties have been studied extensively in an effort to improve its precision and overcome its few limitations. The cross‐correlation technique is widely applied in signal processing in communications, electronics, control sciences, and so on, especially in the analysis of signals that are affected by a shift due to external factors. Under certain assumptions, spectral evaluations through cross‐correlation are equivalent to using maximum likelihood analysis and least‐squares method for the measurements obtained .…”

Section: Introductionmentioning

confidence: 99%

TXRF quantification of interfering heavy metals using deconvolution, cross‐correlation, and external standard calibration

2013

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We developed a general procedure that includes external standard calibration and a deconvolution of spectral signals, which determined with high accuracy the relative proportion and absolute quantification of elements that habitually overlap in total reflection X‐ray fluorescence spectroscopy. The deconvolution proposed takes advantage of the well‐known method of a cross‐correlation technique, offering improvements in identification of simultaneous signals and in the determination of the relative elemental proportions. The external standard calibration was studied determining its range of application for the elements of interest and implemented in certified standard samples producing excellent results for the quantification of the mentioned elements. In this paper, we show the quality of the results obtained for specific heavy metals of currently health and industrial interest in the range of linear response of 0.2–200 ng. Copyright © 2013 John Wiley & Sons, Ltd.

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Spectral and wavelet methods for the analysis of nonlinear and nonstationary time series

Cited by 17 publications

References 17 publications

Exploring the Influence Mechanism of Meteorological Conditions on the Concentration of Suspended Solids and Chlorophyll-a in Large Estuaries Based on MODIS Imagery

Exploring the Influence Mechanism of Meteorological Conditions on the Concentration of Suspended Solids and Chlorophyll-a in Large Estuaries Based on MODIS Imagery

A confidence interval test for the detection of structural breaks

TXRF quantification of interfering heavy metals using deconvolution, cross‐correlation, and external standard calibration

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