969 resultados para Wavelet Analysis


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Discovered in 1963, 3C 273 was the second quasar identified and cataloged in the Third Cambridge Catalog for radio sources, and the first one for which emission lines were identified with a hydrogen sequence redshifted. It is the brightest quasar of the celestial sphere, the most studied, analyzed, and with a resulting abundance of data available in a vast literature. The accurate analysis of the deviations of the spectral lines of quasars provides enough information to put in evidence the variation of fundamental constants of nature and similarly the universe expansion rate. The analysis of the variability of the light curves of these bodies, and the consequent accuracy of their periodicity, is of utmost importance as it provides an efficiency of their observations, enables a greater understanding of the physical phenomena, and makes it possible to conduct spectral observations on more accurate dates (when their light curves show pronounced peaks and therefore richer spectra information). In this master’s thesis twenty eight light curves from the quasar 3C 273 are studied, covering all the electromagnetic spectrum wavebands (radio emission to gamma rays), totaling in the analysis of four light curves for each waveband. We have applied the method of Continuous Wavelet Transform using the sixth-order (!0 = 6) Morlet wavelet function, and obtained excellent results in accordance with the literature.

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Binary systems are key environments to study the fundamental properties of stars. In this work, we analyze 99 binary systems identified by the CoRoT space mission. From the study of the phase diagrams of these systems, our sample is divided into three groups: those whose systems are characterized by the variability relative to the binary eclipses; those presenting strong modulations probably due to the presence of stellar spots on the surface of star; and those whose systems have variability associated with the expansion and contraction of the surface layers. For eclipsing binary stars, phase diagrams are used to estimate the classification in regard to their morphology, based on the study of equipotential surfaces. In this context, to determine the rotation period, and to identify the presence of active regions, and to investigate if the star exhibits or not differential rotation and study stellar pulsation, we apply the wavelet procedure. The wavelet transform has been used as a powerful tool in the treatment of a large number of problems in astrophysics. Through the wavelet transform, one can perform an analysis in time-frequency light curves rich in details that contribute significantly to the study of phenomena associated with the rotation, the magnetic activity and stellar pulsations. In this work, we apply Morlet wavelet (6th order), which offers high time and frequency resolution and obtain local (energy distribution of the signal) and global (time integration of local map) wavelet power spectra. Using the wavelet analysis, we identify thirteen systems with periodicities related to the rotational modulation, besides the beating pattern signature in the local wavelet map of five pulsating stars over the entire time span.

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Binary systems are key environments to study the fundamental properties of stars. In this work, we analyze 99 binary systems identified by the CoRoT space mission. From the study of the phase diagrams of these systems, our sample is divided into three groups: those whose systems are characterized by the variability relative to the binary eclipses; those presenting strong modulations probably due to the presence of stellar spots on the surface of star; and those whose systems have variability associated with the expansion and contraction of the surface layers. For eclipsing binary stars, phase diagrams are used to estimate the classification in regard to their morphology, based on the study of equipotential surfaces. In this context, to determine the rotation period, and to identify the presence of active regions, and to investigate if the star exhibits or not differential rotation and study stellar pulsation, we apply the wavelet procedure. The wavelet transform has been used as a powerful tool in the treatment of a large number of problems in astrophysics. Through the wavelet transform, one can perform an analysis in time-frequency light curves rich in details that contribute significantly to the study of phenomena associated with the rotation, the magnetic activity and stellar pulsations. In this work, we apply Morlet wavelet (6th order), which offers high time and frequency resolution and obtain local (energy distribution of the signal) and global (time integration of local map) wavelet power spectra. Using the wavelet analysis, we identify thirteen systems with periodicities related to the rotational modulation, besides the beating pattern signature in the local wavelet map of five pulsating stars over the entire time span.

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Thyristor-based onload tap-changing ac voltage stabilizers are cheap and robust. They have replaced most mechanical tap-changers in low voltage applications from 300 VA to 300 M. Nevertheless, this replacement hardily applies to tap-changers associated to transformers feeding medium-voltage lines (typically 69 kV primary, 34.5 kV line, 10 MVA) which need periodical maintenance of contacts and oil. The Electric Power Research Institute (EPRI) has studied the feasibility of this replacement. It detected economical problems derived from the need for series association of thyristors to manage the high voltages involved, and from the current overload developed under line fault. The paper reviews the configurations used in that field and proposes new solutions, using a compensating transformer in the main circuit and multi-winding coils in the commutating circuit, with reduced overload effect and no series association of thyristors, drastically decreasing their number and rating. The stabilizer can be installed at any point of the line and the electronic circuit can be fixed to ground. Subsequent works study and synthesize several commutating circuits in detail.

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Proceedings of the Sixth Portuguese Conference on Bioemedical Engineering faro, Portugal

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Under the pseudoinverse control, robots with kinematical redundancy exhibit an undesirable chaotic joint motion which leads to an erratic behavior. This paper studies the complexity of fractional dynamics of the chaotic response. Fourier and wavelet analysis provides a deeper insight, helpful to know better the lack of repeatability problem of redundant manipulators. This perspective for the study of the chaotic phenomena will permit the development of superior trajectory control algorithms.

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In today’s healthcare paradigm, optimal sedation during anesthesia plays an important role both in patient welfare and in the socio-economic context. For the closed-loop control of general anesthesia, two drugs have proven to have stable, rapid onset times: propofol and remifentanil. These drugs are related to their effect in the bispectral index, a measure of EEG signal. In this paper wavelet time–frequency analysis is used to extract useful information from the clinical signals, since they are time-varying and mark important changes in patient’s response to drug dose. Model based predictive control algorithms are employed to regulate the depth of sedation by manipulating these two drugs. The results of identification from real data and the simulation of the closed loop control performance suggest that the proposed approach can bring an improvement of 9% in overall robustness and may be suitable for clinical practice.

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In today’s healthcare paradigm, optimal sedation during anesthesia plays an important role both in patient welfare and in the socio-economic context. For the closed-loop control of general anesthesia, two drugs have proven to have stable, rapid onset times: propofol and remifentanil. These drugs are related to their effect in the bispectral index, a measure of EEG signal. In this paper wavelet time–frequency analysis is used to extract useful information from the clinical signals, since they are time-varying and mark important changes in patient’s response to drug dose. Model based predictive control algorithms are employed to regulate the depth of sedation by manipulating these two drugs. The results of identification from real data and the simulation of the closed loop control performance suggest that the proposed approach can bring an improvement of 9% in overall robustness and may be suitable for clinical practice.

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The autonomic nervous system (ANS) is known to be an important modulator in the pathogenesis of paroxysmal atrial fibrillation (PAF). Changes in ANS control of heart rate variability (HRV) occur during orthostatism to maintain cardiovascular homeostasis. Wavelet transform has emerged as a useful tool that provides time-frequency decomposition of the signal under investigation, enabling intermittent components of transient phenomena to be analyzed. AIM: To study HRV during head-up tilt (HUT) with wavelet transform analysis in PAF patients and healthy individuals (normals). METHODS: Twenty-one patients with PAF (8 men; age 58 +/- 14 yrs) were examined and compared with 21 normals (7 men, age 48 +/- 12 yrs). After a supine resting period, all subjects underwent passive HUT (60 degrees) while in sinus rhythm. Continuous monitoring of ECG and blood pressure was carried out (Task Force Monitor, CNSystems). Acute changes in RR-intervals were assessed by wavelet analysis and low-frequency power (LF: 0.04-0.15 Hz), high-frequency power (HF: 0.15-0.60 Hz) and LF/HF (sympathovagal) were calculated for 1) the last 2 min of the supine period; 2) the 15 sec of tilting movement (TM); and 3) the 1st (TT1) and 2nd (TT2) min of HUT. Data are expressed as means +/- SEM. RESULTS: Baseline and HUT RR-intervals were similar for the two groups. Supine basal blood pressure was also similar for the two groups, with a sustained increase in PAF patients, and a decrease followed by an increase and then recovery in normals. Basal LF, HF and LF/ HF values in PAF patients were 632 +/- 162 ms2, 534 +/- 231 ms2 and 1.95 +/- 0.39 respectively, and 1058 +/- 223 ms2, 789 +/- 244 ms2 and 2.4 +/- 0.36 respectively in normals (p = NS). During TM, LF, HF and LF/HF values for PAF patients were 747 +/- 277 ms2, 387 +/- 94 ms2 and 2.9 +/- 0.6 respectively, and 1316 +/- 315 ms2, 698 +/- 148 ms2 and 2.8 +/- 0.6 respectively in normals (p < 0.05 for LF and HF). During TF1, LF, HF and LF/ HF values for PAF patients were 1243 +/- 432 ms2, 302 +/- 88 ms2 and 7.7 +/- 2.4 respectively, and 1992 +/- 398 ms2, 333 +/- 76 ms2 and 7.8 +/- 0.98 respectively for normals (p < 0.05 for LF). During TF2, LF, HF and LF/HF values for PAF patients were 871 +/- 256 ms2, 242 +/- 51 ms2 and 4.7 +/- 0.9 respectively, and 1263 +/- 335 ms2, 317 +/- 108 ms2 and 8.6 +/- 0.68 respectively for normals (p < 0.05 for LF/HF). The dynamic profile of HRV showed that LF and HF values in PAF patients did not change significantly during TM or TT2, and LF/HF did not change during TM but increased in TT1 and TT2. CONCLUSION: Patients with PAF present alterations in HRV during orthostatism, with decreased LF and HF power during TM, without significant variations during the first minutes of HUT. These findings suggest that wavelet transform analysis may provide new insights when assessing autonomic heart regulation and highlight the presence of ANS disturbances in PAF.

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\The idea that social processes develop in a cyclical manner is somewhat like a `Lorelei'. Researchers are lured to it because of its theoretical promise, only to become entangled in (if not wrecked by) messy problems of empirical inference. The reasoning leading to hypotheses of some kind of cycle is often elegant enough, yet the data from repeated observations rarely display the supposed cyclical pattern. (...) In addition, various `schools' seem to exist which frequently arrive at di erent conclusions on the basis of the same data." (van der Eijk and Weber 1987:271). Much of the empirical controversies around these issues arise because of three distinct problems: the coexistence of cycles of di erent periodicities, the possibility of transient cycles and the existence of cycles without xed periodicity. In some cases, there are no reasons to expect any of these phenomena to be relevant. Seasonality caused by Christmas is one such example (Wen 2002). In such cases, researchers mostly rely on spectral analysis and Auto-Regressive Moving-Average (ARMA) models to estimate the periodicity of cycles.1 However, and this is particularly true in social sciences, sometimes there are good theoretical reasons to expect irregular cycles. In such cases, \the identi cation of periodic movement in something like the vote is a daunting task all by itself. When a pendulum swings with an irregular beat (frequency), and the extent of the swing (amplitude) is not constant, mathematical functions like sine-waves are of no use."(Lebo and Norpoth 2007:73) In the past, this di culty has led to two di erent approaches. On the one hand, some researchers dismissed these methods altogether, relying on informal alternatives that do not meet rigorous standards of statistical inference. Goldstein (1985 and 1988), studying the severity of Great power wars is one such example. On the other hand, there are authors who transfer the assumptions of spectral analysis (and ARMA models) into fundamental assumptions about the nature of social phenomena. This type of argument was produced by Beck (1991) who, in a reply to Goldstein (1988), claimed that only \ xed period models are meaningful models of cyclic phenomena".We argue that wavelet analysis|a mathematical framework developed in the mid-1980s (Grossman and Morlet 1984; Goupillaud et al. 1984) | is a very viable alternative to study cycles in political time-series. It has the advantage of staying close to the frequency domain approach of spectral analysis while addressing its main limitations. Its principal contribution comes from estimating the spectral characteristics of a time-series as a function of time, thus revealing how its di erent periodic components may change over time. The rest of article proceeds as follows. In the section \Time-frequency Analysis", we study in some detail the continuous wavelet transform and compare its time-frequency properties with the more standard tool for that purpose, the windowed Fourier transform. In the section \The British Political Pendulum", we apply wavelet analysis to essentially the same data analyzed by Lebo and Norpoth (2007) and Merrill, Grofman and Brunell (2011) and try to provide a more nuanced answer to the same question discussed by these authors: do British electoral politics exhibit cycles? Finally, in the last section, we present a concise list of future directions.

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Respiratory syncytial virus (RSV) infection is the leading cause of hospitalisation for respiratory diseases among children under 5 years old. The aim of this study was to analyse RSV seasonality in the five distinct regions of Brazil using time series analysis (wavelet and Fourier series) of the following indicators: monthly positivity of the immunofluorescence reaction for RSV identified by virologic surveillance system, and rate of hospitalisations per bronchiolitis and pneumonia due to RSV in children under 5 years old (codes CID-10 J12.1, J20.5, J21.0 and J21.9). A total of 12,501 samples with 11.6% positivity for RSV (95% confidence interval 11 - 12.2), varying between 7.1 and 21.4% in the five Brazilian regions, was analysed. A strong trend for annual cycles with a stable stationary pattern in the five regions was identified through wavelet analysis of the indicators. The timing of RSV activity by Fourier analysis was similar between the two indicators analysed and showed regional differences. This study reinforces the importance of adjusting the immunisation period for high risk population with the monoclonal antibody palivizumab taking into account regional differences in seasonality of RSV.

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This study aimed to describe the probabilistic structure of the annual series of extreme daily rainfall (Preabs), available from the weather station of Ubatuba, State of São Paulo, Brazil (1935-2009), by using the general distribution of extreme value (GEV). The autocorrelation function, the Mann-Kendall test, and the wavelet analysis were used in order to evaluate the presence of serial correlations, trends, and periodical components. Considering the results obtained using these three statistical methods, it was possible to assume the hypothesis that this temporal series is free from persistence, trends, and periodicals components. Based on quantitative and qualitative adhesion tests, it was found that the GEV may be used in order to quantify the probabilities of the Preabs data. The best results of GEV were obtained when the parameters of this function were estimated using the method of maximum likelihood. The method of L-moments has also shown satisfactory results.

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The objective of the present study is to understand the spatial and temporal variability of sea surface temperature(SST), precipitable water, zonal and meridional components of wind stress over the tropical Indian Ocean to understand the different scales of variability of these features of Indian Ocean. Empirical Orthogonal Function (EOF) and wavelet analysis techniques are utilized to understand the standing oscillations and multi scale oscillations respectively. The study has been carried out over Indian Ocean and South Indian Ocean. For the present study, NCEP/NCAR(National Center for Environmental Prediction National Center for Atmospheric Research) reanalyzed daily fields of sea surface temperature, zonal and meridional surface wind components and precipitable water amount during 1960-1998 are used. The principle of EOF analysis and the methodology used for the analysis of spatial and temporal variance modes.

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The present work is an attempt to understand the characteristics of the upper troposphere and lower stratosphere over the Asian summer monsoon region, more specifically over the Indian subcontinent. Mainly three important parameters are taken such as zonal wind, temperature and ozone over the UT/LS of the Asian summer monsoon region. It made a detailed study of its interannual variability and characteristics of theses parameters during the Indian summer monsoon period. Monthly values of zonal wind and temperature from the NCEP/NCAR reanalysis for the period 1960-2002 are used for the present study. Also the daily overpass total ozone data for the 12 Indian stations (from low latitude to high latitudes) from the TOMS Nimbus 7 satellite for the period 1979 to 1992 were also used to understand the total ozone variation over the Indian region. The study reveals that if QBO phases in the stratosphere is easterly or weak westerly then the respective monsoon is found to be DRY or below Normal . On the other hand, if the phase is westerly or weak easterly the respective Indian summer monsoon is noted as a WET year. This connection of stratospheric QBO phases and Indian summer monsoon gives more insight in to the long-term predictions of Indian summer monsoon rainfall. Wavelet analysis and EOF methods are the two advanced statistical techniques used in the present study to explore more information of the zonal wind that from the smaller scale to higher scale variability over the Asian summer monsoon region. The interannual variability of temperature for different stratospheric and tropospheric levels over the Asian summer monsoon region have been studied. An attempt has been made to understand the total ozone characteristics and its interannual variablilty over 12 Indian stations spread from south latitudes to north latitudes. Finally it found that the upper troposphere and lower stratosphere contribute significantly to monsoon variability and climate changes. It is also observed that there exists a link between the stratospheric QBO and Indian summer monsoon

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Mann–Kendall non-parametric test was employed for observational trend detection of monthly, seasonal and annual precipitation of five meteorological subdivisions of Central Northeast India (CNE India) for different 30-year normal periods (NP) viz. 1889–1918 (NP1), 1919–1948 (NP2), 1949–1978 (NP3) and 1979–2008 (NP4). The trends of maximum and minimum temperatures were also investigated. The slopes of the trend lines were determined using the method of least square linear fitting. An application of Morelet wavelet analysis was done with monthly rainfall during June– September, total rainfall during monsoon season and annual rainfall to know the periodicity and to test the significance of periodicity using the power spectrum method. The inferences figure out from the analyses will be helpful to the policy managers, planners and agricultural scientists to work out irrigation and water management options under various possible climatic eventualities for the region. The long-term (1889–2008) mean annual rainfall of CNE India is 1,195.1 mm with a standard deviation of 134.1 mm and coefficient of variation of 11%. There is a significant decreasing trend of 4.6 mm/year for Jharkhand and 3.2 mm/day for CNE India. Since rice crop is the important kharif crop (May– October) in this region, the decreasing trend of rainfall during themonth of July may delay/affect the transplanting/vegetative phase of the crop, and assured irrigation is very much needed to tackle the drought situation. During themonth of December, all the meteorological subdivisions except Jharkhand show a significant decreasing trend of rainfall during recent normal period NP4. The decrease of rainfall during December may hamper sowing of wheat, which is the important rabi crop (November–March) in most parts of this region. Maximum temperature shows significant rising trend of 0.008°C/year (at 0.01 level) during monsoon season and 0.014°C/year (at 0.01 level) during post-monsoon season during the period 1914– 2003. The annual maximum temperature also shows significant increasing trend of 0.008°C/year (at 0.01 level) during the same period. Minimum temperature shows significant rising trend of 0.012°C/year (at 0.01 level) during postmonsoon season and significant falling trend of 0.002°C/year (at 0.05 level) during monsoon season. A significant 4– 8 years peak periodicity band has been noticed during September over Western UP, and 30–34 years periodicity has been observed during July over Bihar subdivision. However, as far as CNE India is concerned, no significant periodicity has been noticed in any of the time series.