Relevant bibliographies by topics / Continuous wavelet analysis

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Continuous wavelet analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "Continuous wavelet analysis"

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Abdullah, Shahrum, S. N. Sahadan, Mohd Zaki Nuawi, and Zulkifli Mohd Nopiah. "Fatigue Data Analysis Using Continuous Wavelet Transform and Discrete Wavelet Transform." Key Engineering Materials 462-463 (January 2011): 461–66. http://dx.doi.org/10.4028/www.scientific.net/kem.462-463.461.

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The wavelet transform is well known for its ability in vibration analysis in fault detection. This paper presents the ability of wavelet transform in fatigue data analysis starts from high amplitude events detection and it is then followed by fatigue data extraction based on wavelet coefficients. Since the wavelet transform has two main categories, i.e. the continuous wavelet transforms (CWT) and the discrete wavelet transform (DWT), the comparison study were carried out in order to investigate performance of both wavelet for fatigue data analysis. CWT represents by the Morlet wavelet while DWT with the form of the 4th Order Daubechies wavelet (Db4) was also used for the analysis. An analysis begins with coefficients plot using the time-scale representation that associated to energy coefficients plot for the input value in fatigue data extraction. Ten extraction levels were used and all levels gave the damage difference, (%∆D) less than 10% with respect to original signal. From the study, both wavelet transforms gave almost similar ability in editing fatigue data but the Morlet wavelet provided faster analysis time compared to the Db4 wavelet. In comparison to have the value of different at 5%, the Morlet wavelet achieved at L= 5 while the Db4 wavelet at L=7. Even though it gave slower analysis time, both wavelets can be used in fatigue data editing but at different time consuming.
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Stark, Hans-Georg. "Continuous wavelet transform and continuous multiscale analysis." Journal of Mathematical Analysis and Applications 169, no. 1 (September 1992): 179–96. http://dx.doi.org/10.1016/0022-247x(92)90110-y.

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Wachowiak, Mark P., Renata Wachowiak-Smolíková, Michel J. Johnson, Dean C. Hay, Kevin E. Power, and F. Michael Williams-Bell. "Quantitative feature analysis of continuous analytic wavelet transforms of electrocardiography and electromyography." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 376, no. 2126 (July 9, 2018): 20170250. http://dx.doi.org/10.1098/rsta.2017.0250.

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Theoretical and practical advances in time–frequency analysis, in general, and the continuous wavelet transform (CWT), in particular, have increased over the last two decades. Although the Morlet wavelet has been the default choice for wavelet analysis, a new family of analytic wavelets, known as generalized Morse wavelets, which subsume several other analytic wavelet families, have been increasingly employed due to their time and frequency localization benefits and their utility in isolating and extracting quantifiable features in the time–frequency domain. The current paper describes two practical applications of analysing the features obtained from the generalized Morse CWT: (i) electromyography, for isolating important features in muscle bursts during skating, and (ii) electrocardiography, for assessing heart rate variability, which is represented as the ridge of the main transform frequency band. These features are subsequently quantified to facilitate exploration of the underlying physiological processes from which the signals were generated. This article is part of the theme issue ‘Redundancy rules: the continuous wavelet transform comes of age’.
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Gulai, A. V., and V. M. Zaitsev. "INTELLIGENT TECHNOLOGY OF WAVELET ANALYSIS OF VIBRATION SIGNALS." Doklady BGUIR, no. 7-8 (December 29, 2019): 101–8. http://dx.doi.org/10.35596/1729-7648-2019-126-8-101-108.

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During solution of engineering problems of machinery dynamics a need of revealing the harmonic components often arises in the narrow timing gate. This requires the use of wavelet-transformation oscillation methods and introduction of intelligent systems to hardware and software used in the experiment. The wavelet is considered as a short in time signal functional window, which has its internal structure in the form of a fading wavelike burst, and it is characterized by a scale of display of certain events in the field of the signal frequency spectrum, as well as and by time axis shifts. Complex-functioned continuous functions of real arguments (Daubechies wavelets, Gaussian wavelets, MHat-wavelets), complex-valued functions of real arguments (Morlet and Paul wavelets), as well as real discrete functions (HААRT- and FHat-wavelets) are used as wavelet functions. The wavelet analysis method of vibration signals is disclosed at acoustic diagnostics of machines and mechanisms. Digital implementation of discrete indications of wavelets with the subsequent visualization of results in the form of scalotons is the mathematical basis of the algorithm for procession of vibration signals. It has been suggested that engineering analysis and reconstruction of signals should be implemented by means of directed and reverse continuous wavelet conversions, which are discrete by arguments. The structural and functional scheme of the multichannel system of the intelligent wavelet analysis of vibration signals in machines has been considered. The intelligent system for study of vibration signals makes it possible to form the totality of photographic parameters, when scalotons are calculated by wavelet functions. An example of experimental implementation of the wavelet conversion method of vibration signals parameters is shown. Results of scalotons calculation are shown, when MHat-wavelet and DOG-wavelet are used.
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Qin, Jun, and Pengfei Sun. "Applications and Comparison of Continuous Wavelet Transforms on Analysis of A-wave Impulse Noise." Archives of Acoustics 40, no. 4 (December 1, 2015): 503–12. http://dx.doi.org/10.1515/aoa-2015-0050.

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Abstract Noise induced hearing loss (NIHL) is a serious occupational related health problem worldwide. The A-wave impulse noise could cause severe hearing loss, and characteristics of such kind of impulse noise in the joint time-frequency (T-F) domain are critical for evaluation of auditory hazard level. This study focuses on the analysis of A-wave impulse noise in the T-F domain using continual wavelet transforms. Three different wavelets, referring to Morlet, Mexican hat, and Meyer wavelets, were investigated and compared based on theoretical analysis and applications to experimental generated A-wave impulse noise signals. The underlying theory of continuous wavelet transform was given and the temporal and spectral resolutions were theoretically analyzed. The main results showed that the Mexican hat wavelet demonstrated significant advantages over the Morlet and Meyer wavelets for the characterization and analysis of the A-wave impulse noise. The results of this study provide useful information for applying wavelet transform on signal processing of the A-wave impulse noise.
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Alhasan, Ahmad, David J. White, and Kris De Brabanterb. "Continuous wavelet analysis of pavement profiles." Automation in Construction 63 (March 2016): 134–43. http://dx.doi.org/10.1016/j.autcon.2015.12.013.

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Lee, Sang Kwon, and Jang Sun Sim. "Development of Spike Wavelet Analysis and Its Application to Damage Analysis on Gearbox." Key Engineering Materials 321-323 (October 2006): 1233–36. http://dx.doi.org/10.4028/www.scientific.net/kem.321-323.1233.

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Impulsive sound and vibration signals in gear system are often associated with their faults. Thus these impulsive sound and vibration signals can be used as indicators in condition monitoring of gear system. The traditional continuous wavelet transform has been used for detection of impulsive signals. However, it is often difficult for the continuous wavelet transform to identify spikes at high frequency and meshing frequencies at low frequency simultaneously since the continuous wavelet transform is to apply the linear scaling (a-dilation) to the mother wavelet. In this paper, the spike wavelet transform is developed to extract these impulsive sound and vibration signals. Since the spike wavelet transform is to apply the non-linear scaling, it has better time resolution at high frequency and frequency resolution at low frequency than that of the continuous wavelet transform respectively. The spike wavelet transform can be, therefore, used to detect fault position clearly without the loss of information for the damage of a gear system. The spike wavelet transform is successfully is applied to detection of the gear fault with tip breakage.
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Lin, En-Bing, and Paul C. Liu. "A discrete wavelet analysis of freak waves in the ocean." Journal of Applied Mathematics 2004, no. 5 (2004): 379–94. http://dx.doi.org/10.1155/s1110757x0430611x.

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A freak wave is a wave of very considerable height, ahead of which there is a deep trough. A case study examines some basic properties developed by performing wavelet analysis on a freak wave. We demonstrate several applications of wavelets and discrete and continuous wavelet transforms on the study of a freak wave. A modeling setting for freak waves will also be mentioned.
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STASZEWSKI, W. J., and K. WORDEN. "WAVELET ANALYSIS OF TIME-SERIES: COHERENT STRUCTURES, CHAOS AND NOISE." International Journal of Bifurcation and Chaos 09, no. 03 (March 1999): 455–71. http://dx.doi.org/10.1142/s0218127499000304.

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The continuous and orthogonal wavelet transforms are used to analyze time-series data. The analysis involves signal decomposition into scale components using both Grossman–Morlet and Daubechies type wavelets. A number of simulated and experimental data vectors exhibiting different types of coherent structures, chaos and noise is analyzed. The study shows that wavelet analysis provides a unifying framework for the description of many phenomena in time-series.
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Ji, Ning, Hui Zhou, Kaifeng Guo, Oluwarotimi Samuel, Zhen Huang, Lisheng Xu, and Guanglin Li. "Appropriate Mother Wavelets for Continuous Gait Event Detection Based on Time-Frequency Analysis for Hemiplegic and Healthy Individuals." Sensors 19, no. 16 (August 8, 2019): 3462. http://dx.doi.org/10.3390/s19163462.

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Gait event detection is a crucial step towards the effective assessment and rehabilitation of motor dysfunctions. Recently, the continuous wavelet transform (CWT) based methods have been increasingly proposed for gait event detection due to their robustness. However, few investigations on determining the appropriate mother wavelet with proper selection criteria have been performed, especially for hemiplegic patients. In this study, the performances of commonly used mother wavelets in detecting gait events were systematically investigated. The acceleration signals from the tibialis anterior muscle of both healthy and hemiplegic subjects were recorded during ground walking and the two core gait events of heel strike (HS) and toe off (TO) were detected from the signal recordings by a CWT algorithm with different mother wavelets. Our results showed that the overall performance of the CWT algorithm in detecting the two gait events was significantly different when using various mother wavelets. By using different wavelet selection criteria, we also found that the accuracy criteria based on time-error minimization and F1-score maximization could provide the appropriate mother wavelet for gait event detection. The findings from this study will provide an insight on the selection of an appropriate mother wavelet for gait event detection and facilitate the development of adequate rehabilitation aids.
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Dissertations / Theses on the topic "Continuous wavelet analysis"

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Bunluechokchai, Sonthaya. "Wavelet analysis of the high resolution electrocardiogram for the detection of ventricular late potentials." Thesis, University of Sussex, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.288618.

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The High Resolution Electrocardiogram (HRECG) is used to detect Ventricular Late Potentials (VLPs) in post-myocardial infarction patients. VLPs are low-amplitude, high-frequency signals that are usually found within the terminal part of the QRS complex. The aim of this research was to develop possible alternative methods and improve existing methods of detecting VLP activity. There are two main topics in this work: applications of the Continuous Wavelet Transform (CWT) and the Discrete Wavelet Transform (DWT) to the HRECG. For the CWT application, a Fractionation Factor (FF) method proposed by previous work was further investigated and improved by combining the CWT and DWT for distinction between patients with and those without VLPs. A Differential Fractionation Factor was proposed as an alternative approach to the FF with better results. Observation in the time-scale plot showed a difference in the energy distribution. A 2-dimensional Fractionation Factor was proposed to quantify this difference. A new concept of local intermittency was investigated to exhibit energy nonuniformity and then a Local Intermittency Factor was developed to quantify the degree of nonuniformity. The energy computed with the CWT was also used for patient distinction. Patients with VLPs may be also characterised by a slow rate of energy decay. The CWT can reveal a difference in ECG irregularity between the patients. A new approach of approximate entropy was implemented to quantify this irregularity. For the DWT application, the DWT can reveal irregularity of VLP activity and it was quantified by the approximate entropy to identify patients with VLPs. The wavelet entropy was utilised as an alternative method to the FF. The energy computed with the DWT was used for patient classification. The potentially promising results of both the CWT and DWT applications were obtained from the methods of computing the energy and approximate entropy
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Tse, Chung Fai Norman. "The development of complex continuous wavelet transform based harmonic analysis and dynamic waveform reconstruction algorithms." Thesis, City University London, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.446448.

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Jaskowak, Daniel Joseph. "Detecting Transient Changes in Gait Using Fractal Scaling of Gait Variability in Conjunction with Gaussian Continuous Wavelet Transform." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/87393.

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Accelerometer data can be analyzed using a variety of methods which are effective in the clinical setting. Time-series analysis is used to analyze spatiotemporal variables in various populations. More recently, investigators have focused on gait complexity and the structure of spatiotemporal variations during walking and running. This study evaluated the use of time-series analyses to determine gait parameters during running. Subjects were college-age female soccer players. Accelerometer data were collected using GPS-embedded trunk-mounted accelerometers. Customized Matlab® programs were developed that included Gaussian continuous wavelet transform (CWT) to determine spatiotemporal characteristics, detrended fluctuation analysis (DFA) to examine gait complexity and autocorrelation analyses (ACF) to assess gait regularity. Reliability was examined using repeated running efforts and intraclass correlation. Proof of concept was determined by examining differences in each variable between various running speeds. Applicability was established by examining gait before and after fatiguing activity. The results showed most variables had excellent reliability. Test-retest R2 values for these variables ranged from 0.8 to 1.0. Low reliability was seen in bilateral comparisons of gait symmetry. Increases in running speed resulted in expected changes in spatiotemporal and acceleration variables. Fatiguing exercise had minimal effects on spatiotemporal variables but resulted in noticeable declines in complexity. This investigation shows that GPS-embedded trunk-mounted accelerometers can be effectively used to assess running gait. CWT and DFA yield reliable measures of spatiotemporal characteristics of gait and gait complexity. The effects of running speed and fatigue on these variables provides proof of concepts and applicability for this analytical approach.
Master of Science
Fitness trackers have become widely accessible and easy to use. So much so that athletic teams have been using them to track activity throughout the season. Researchers are able to manipulate data generated from the fitness monitors to assess many different variables including gait. Monitoring gait may generate important information about the condition of the individual. As a person fatigues, running form is theorized to breakdown, which increases injury risk. Therefore the ability to monitor gait may be advantageous in preventing injury. The purpose of this study is to show that the methods in this study are reproducible, respond reasonably to changes in speed, and to observe the changes of gait in the presence of fatigue or on tired legs. Three analyses are used in this study. The first method called autocorrelation, overlays acceleration signals of consecutive foot strikes, and determines the similarity between them. The second method utilizes a wave transformation technique that is able to determine foot contact times. The final method attempts to determine any pattern in the running stride. This method looks for changes in the structure of the pattern. Less structure would indicate a stride that is fatigued. The results showed that the methods of gait analysis used in this study were reproducible and responded appropriately with changes in speed. Small changes in gait were observed due to the presence of fatigue. Further investigation into the use of these methods to determine changes in gait due to the presence of fatigue are warranted.
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Maraun, Douglas. "What can we learn from climate data? : Methods for fluctuation, time/scale and phase analysis." Phd thesis, [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=981698980.

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Helienek, Matúš. "Simulační a experimentální analýza řezání kotoučovou pilou." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2018. http://www.nusl.cz/ntk/nusl-412924.

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This thesis deals with analysis of dynamic forces and vibrations created during cutting with saw. The analysis is done on both simulation and experimental level. Acquired signals are evaluated with signal tools as STFT, CWT and DWT.
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Zamrane, Zineb. "Recherche d’indices de variabilité climatique dans des séries hydroclmatiques au Maroc : identification, positionnement temporel, tendances et liens avec les fluctuations climatiques : cas des grands bassins de la Moulouya, du Sebou et du Tensift." Thesis, Montpellier, 2016. http://www.theses.fr/2016MONTT181/document.

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Ce travail consiste à caractériser la variabilité temporelle et spatiale des séries chronologiques de paramètres hydroclimatiques (pluies, débits) au niveau de trois grand bassins au Maroc ; (bassins de la Moulouya, du Sebou et du Tensift) et à chercher les liens entre cette variabilité hydrologique et les fluctuations climatiques matérialisées par différents indices climatiques, NAO, SOI, WMOI. L’approche d’étude est basée le traitement statistique des séries temporelles, liée aux dimensions temps et espace.Les grands bassins versants d'échelle continentale comme le Tensift, le Sebou et la Moulouya en climat méditerranéen sous influence océanique, intègrent sur des grandes surfaces la réponse hydrologique aux changements climatiques et environnementaux (fluctuations du climat, précipitations, débits) à de larges échelles spatiales et temporelles, mais également les modifications du milieu physique d’origine anthropique (changements d’occupation des sols, aménagements…), ce qui rend parfois difficile l’identification des liens entre la variabilité hydrologique et la variabilité climatique. Les principaux objectifs de ce travail sont de déterminer et de quantifier les relations entre la variabilité hydroclimatique et les fluctuations du climat à l’échelle de chaque bassin étudié et de ses principaux sous-bassins, via l'utilisation de méthodes d’analyses spectrales adaptées à l’étude des processus non stationnaires (analyse en ondelettes continues, analyse de la cohérence par ondelettes). Plusieurs modes de variabilités sont identifiés à partir de l’analyse par station (pluies et débits), du cycle annuel au mode 16-22 ans, cette analyse sera complétée par une analyse par maille, dont les données sont issues d’un fichier (SIEREM) couvrant la période 1940-1999, où on identifie des fréquences de 1an au 8-16 ans, distinguées sur des périodes différentes au niveau de chaque bassin, permettant ainsi une décomposition de la variabilité spatiale des signaux mis en évidence. Trois principales discontinuités sont identifiées en 1970, 1980 et 2000. La contribution des indices climatiques est assez importante elle est entre 55% et 80%
This work is to characterize the temporal and spatial variability of hydroclimatic time series (rainfall, flow) at three large basins in Morocco; (basins of the Sebou and Moulouya Tensift) and look links between the hydrologic variability and climate fluctuation materialized by various climate indices, NAO, SOI, WMOI. The approach to study is based on statistical analysis of time series, related to time and space dimensions.The great watershed of continental scale as Tensift, Sebou and Moulouya in Mediterranean climate under oceanic influence, integrate over large areas the hydrological response to climate and environmental changes (climate fluctuations, precipitation, flows) not only to large spatial and temporal scales, but also to changes in the physical environment anthropogenic (land use changes, developments ...), which sometimes makes difficult to identify the links between hydrological variability and climate variability. The main objective of this work is to determine and quantify the relationships between hydrological variability and climate fluctuations (regionalised precipitation, climate change indexes) across each studied basin and its main sub-basins, via using spectral analysis methods adapted to the study of non-stationary processes (continuous wavelet analysis, coherence analysis wavelet). Many modes of variability are identified from the station analysis (rainfall and flow rates), the annual cycle to 16-22 years, this analysis will be complemented by a grid analysis, the data come from a (SIEREM) file covering the period from 1940 to 1999, which will allow a better understanding of the spatial variability of signals set highlighted. Which is identified frequencies the 1 year 8-16 years, distinguished different time periods at each basin, three main discontinuities identified in 1970, 1980 and 2000. The contribution of climatic indices is important enough it is between 55% and 80%
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Bassani, Thiago. "Design of a BCI system using EEG signal analysis with continuous wavelet transformation and Naïves bayes classifier / Thiago Bassani ; orientador, Julio Cesar Nievola." reponame:Biblioteca Digital de Teses e Dissertações da PUC_PR, 2009. http://www.biblioteca.pucpr.br/tede/tde_busca/arquivo.php?codArquivo=1482.

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Dissertação (mestrado) - Pontifícia Universidade Católica do Paraná, Curitiba, 2009
Bibliografia: f. 47-52
Uma das questões mais importantes na interface de computador-cérebro é a análise de padrões cerebrais, geralmente representados por sinais elétricos. Este trabalho tem como objetivo introduzir uma ferramenta de mineração de dados para sinais de EEG, anali
One of the most important issues in brain-computer interface (BCI) is the analysis of patterns in brain states generally represented by electrical signals. The main objective of this work is to present an exploratory approach on electroencephalographic (E
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Pereira, André Luis Vinagre. "Manutenção preditiva de um par engrenado através da análise de lubrificantes e da análise de vibrações utilizando a transformada de wavelet." Universidade Estadual Paulista (UNESP), 2018. http://hdl.handle.net/11449/153304.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Na manutenção preditiva, as análises dos sinais de vibração e das partículas do óleo são frequentemente utilizadas para o diagnóstico de falhas em redutores, porque elas contêm informações das condições de seus elementos mecânicos. Os sinais de vibração de um redutor geralmente têm muito ruído e a relação sinal-ruído é tão baixa que a extração de informações dos componentes do sinal é muito difícil, especialmente em situações práticas. Uma das soluções para este problema é a aplicação de técnicas de processamento do sinal para facilitar a obtenção de informações. Neste trabalho, uma técnica de cancelamento de ruído, a média temporal síncrona (TSA), e outra técnica da transformada contínua de wavelet de Morlet foram desenvolvidas para extração de recursos e diagnóstico de diferentes tipos de danos locais da engrenagem. Estas técnicas são aplicadas em sinais medidos em uma bancada experimental, que consiste em um par engrenado acoplado a um motor e a um gerador. Outro método para monitorar o estado do sistema é pela análise de partículas presente no óleo provenientes do desgaste das engrenagens. Avaliando a quantidade, formato, tamanho e material das partículas é possível obter informações das condições do equipamento e do tipo de desgaste ocorrido. Neste trabalho, foram feitas a análise do óleo pelas técnicas da ferrografia e contagem de partículas. A parte experimental deste trabalho foi dividida em dois experimentos. No primeiro experimento as condições de um par engrenado durante toda a sua vida útil foi monitorada, enquanto que no segundo experimento, um entalhe foi feito na raiz do dente simulando uma trinca por fadiga. A análise das partículas de óleo mostrou quais tipos de desgastes estava ocorrendo e a técnica da transformada contínua de wavelet mostrou-se precisa na identificação de falhas em dentes de engrenagens, sendo possível indicar em qual dente a falha estava se desenvolvendo.
At the predictive maintenance, the vibration signals analysis and oil particles analysis are frequently used to diagnose failures in a gearbox, because they contain information about the condition of its mechanic’s elements. The vibration signals of a gearbox usually have a lot of noise and the ratio ‘signal-noise’ is very low, making the extraction of information from the signals component very hard, especially in a practical situation. One of the solutions to this problem is the application of technics of signal processing, to improve the collection of information. At this study, a technique of noise cancellation, Temporal Synchronous Average (TSA) and another technique called continuous transform with the Morlet wavelet were executed for the extraction of resources and diagnostics of different type of gears local damages. Those methods are applied to signals measured on an experimental test stand, consisting of a gearbox with an engine and a generator. Another method for monitoring system wear is by analyzing wear particles in the oil generated due to the wear on the gears. By evaluating the quantity, shape, size and material of the particles it is possible to obtain information about the conditions of the equipment and the type of wear that has occurred. During this work, it was done the analysis of the oil by the techniques of ferrography and particle counting. The experimental part of this study was divided into two experiments. On the first experiment was monitored the conditions of a couple meshed throughout its useful life and in the second was made a notch in the root of the tooth simulating a crack by fatigue. The analysis of the oil particles showed what types of wear was occurring and the technique of the continuous wavelet transform was accurate in the identification of defects in gear's teeth, and it was possible to indicate which tooth was failing.
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Nes, Preben Gråberg. "Edge-Detection in Signals using the Continuous Wavelet-Transform. : Edge-Detection in Medical UltraSound Images." Thesis, Norwegian University of Science and Technology, Department of Mathematical Sciences, 2006. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9498.

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Today, UltraSound (US) images are often used in medical examination and surgery. An improvement of the quality of these US-images will lead to many advantages, which is a big motivation for research on this field. One obstacle in improving the quality of the images is the presence of noise and texture. In order to distinguish this unwanted information from the interesting objects, different techniques can be used. Characteristic features, such as the ability to find vague contours, small objects or edges of small strength, decides if the technique is suitable for analysing noisy signals. This thesis presents different techniques for finding objects in US-images by using the continuous wavelet-transform. One observation from the analysis is that for edge-detectors using the wavelet-transform at a single scale, there is a compromise between accuracy and reliability. One has to choose between detecting small objects or vague contours. At fine scales one is able to detect small objects, but not objects with a vague contour without including redundant information. At coarse scales one is able to detect vague contours without including redundant information, but one will not detect small objects. The Lipschitz-regularity and the length of a maxima-line in the time-scale plane works well to find the points where the signal changes with a long duration, but is less suitable to find small objects and to remove unwanted information. By using the value of the wavelet-transform at several scales, it is possible to find vague contours in images, small objects, and edges of small strength compared to the strength of the noise. Another important observation from the analysis is that use of the circumference of objects is appropriate in order to find the most important objects in an image. Using this information has been very useful with respect to the analysis of US-images. Medical ultra-sound images are in general of varying quality. In addition the quality of a US-image will typically change within the signal, and changes with respect to the quality of the contour of objects and the influence of noise. The technique which in general is most reliable and produces the best representations of the US-images analysed in this thesis, uses information about the amplitude of the wavelet-transform both within and across scales, in addition to information about the circumference of the objects. This combined edge-detector is reliable with respect to represent the important objects in the image, and this representation is often easily obtained by the edge-detector.

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Vu, Phuong Lan. "Altimétrie spatiale, réflectométrie GNSS et surcotes marines." Thesis, Toulouse 3, 2019. http://www.theses.fr/2019TOU30076.

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L'objectif de ce travail a été de développer une méthodologie de télédétection novatrice, s'appuyant sur des plateformes existantes, de suivi des principaux facteurs influençant la dynamique côtière. Lors de mon étude j'ai développé des suivis basés sur un outil classique: l'altimétrie satellitaire. Mon approche s'est appuié sur les nouvelles missions spatiales dont j'ai évalué l'apport sur la zone côtière qui est la plus critique qui est la plus critique du point de vue socio-économique. J'ai plus spécifiquement regardé la façade atlantique entre La Rochelle et Bayonne. Je me suis ensuite intéressée à une technique originale basée sur la réflexion des ondes GNSS (GNSS-R). Ces outils nous permettent de surveiller précisément les diverses ondes de marée et de détecter des phénomènes plus singuliers comme la tempête Xynthia (2010) qui a affectée le Sud de l'Europe. Ces outils démontrent qu'il est possible aussi de suivre la dynamique côtière liée aux variations de houle et son impact sur l'érosion côtière, et même les effets de la forte dépression atmosphérique associée à Xynthia et qui a eu un impact visible sur le niveau local de l'océan atlantique. Ma thèse repose sur deux approches complémentaires basées sur deux échelles d'analyse, l'une globale associée à l'altimétrie satellitaire l'autre plus locale, dédiée à la détection des évènements extrêmes et basée sur le réflectométrie. La première étude s'appuie sur différentes missions altimétriques et nous a permis de suivre les variations du niveau de la mer de la côte atlantique française au Sud du golfe de Gascogne durant la période de 1995-2015. Les données SARAL, dont l'empreinte au sol au de l'ordre de 6 km, montrent qu'il est maintenant possible de s'approcher de la bande côtière jusqu'à ~10km avec une grande précision (~20cm). La seconde application repose sur le GNSS-R que nous avons utilisé pour suivre la partie protégée de la baie de Saint Jean de Luz. Là encore les résultats sont exceptionnels puisqu'ils nous ont permis de suivre l'impact de la tempête Xynthia. J'ai ainsi mis en évidence qu'il était possible avec un seul instrument de suivre les effets des marées, et les effets des surcotes marines qui, associées à l'impact de la pression atmosphérique, donnent une bonne corrélation (R=0.8 entre la composante RC3 et les surcôtes, et R=0.72 avec la pression atmosphérique) durant la tempête. Enfin nous avons aussi regardé ce qui se passe lors de la transition eaux continentales/océaniques pour les deltas du Fleuve Rouge et du Mékong (Vietnam). Et mêmes si les séries temporelles sont assez courtes, les résultats sont plus qu'encourageant puisqu'ils nous ont permis de de suivre les épisodes de crues associées à deux tempêtes tropicales (Mirinae et Nida) et de mesurer le retard entre les chutes de pluies et la propagation de l'onde crue qui montre dans le cas présent un délai de de 48h pour Nida. Grâce au déploiement dans de nombreux pays de réseaux GNSS permanents, cette technique peut être appliquée lorsqu'une station GNSS permanente est située près du rivage. L'approche GNSS-R peut être alors utilisée pour le suivi des variations du niveau de la mer mais aussi l'impact d'évènements extrêmes. Pour cela nous avons utilisé 3 mois d'enregistrements (janv-mars 2010) de la station GNSS de Socoa, pour déterminer les composantes, court terme, de la marée dans les signaux GNSS-R et pour identifier la tempête Xynthia
The objective of this PhD thesis was to develop an innovative remote sensing methodology, based on existing platforms, to monitor the main factors influencing coastal dynamics. We propose monitoring based on a classic tool i.e. satellite altimetry but with a focus on new space missions (SARAL, Sentinel-3). Whose contributions will be evaluated, particularly in the coastal zone, which is the most critical from a socio-economic point of view? I have focused my attention on the French Atlantic coast between La Rochelle and Bayonne. We will also rely on an original technique based on the reflection of GNSS positioning satellites (technical known as GNSS-R). These tools will allow us to precisely monitor the various tidal waves, but they have also allowed us to detect more unusual phenomena such as the extreme event of 2010: the storm Xynthia that affected the coasts of southern Europe. These tools demonstrate that it is also possible will also be able to see to monitor the coastal dynamics related to swell variations and its impact on coastal erosion, and even the effects of the strong atmospheric depression associated with Xynthia, which has had a measurable impact on the local sea level of the Atlantic Ocean. My thesis is focused on two complementary approaches based on two scales of study: the first one is global and used satellite altimetry, the second one is more local and focused on the extreme event detection and it is based on the GNSS reflectometry. The first study, which I carried out, relies on different satellite altimetry missions (ERS-2, Jason- 1/2/3, ENVISAT, SARAL) which allowed us to follow the sea level variations (SSH) from the French Atlantic coast to the south of the Bay of Biscay during the 1995-2015 period. SARAL data, including a footprint of around 6 km, show that it is now possible to approach the coastal fringe up to ~ 10 km with a great precision (RMSE ~ 20 cm). The second application is based on the GNSS-R methodology that we used to track SSH in the inner part of the bay of Saint Jean de Luz - Socoa during the storm Xynthia. Here again the results are exceptional since they allowed us to follow the impact of the storm Xynthia on the local level of the ocean. I thus highlighted that it was possible with only one instrument to follow the effects of the tides, and even the effects of the marine surges which associated to the impact of the atmospheric pressure on the sea level give a good correlation (R = 0.77 between the RC3 component and the surge, and R = 0.73 with the atmospheric pressure) during storm. Finally we also looked at what is happening in the transition between continental and oceanic waters for the deltas of the Red River and Mekong in Vietnam. And, even if the time series are rather short or truncated (Red River) the results are more than encouraging since they allowed us to follow the flooding events associated with two tropical storms (Mirinae and Nida) and to measure the delay between the rain falls and the propagation of the flood wave which shows in this case a delay of 48 h for Nida. With the deployment of permanent GNSS networks in many countries, this technique can be applied when a permanent GNSS station is located near the shore. The GNSS-R approach can be used to monitor sea level variations but also the effect of extreme events. For that we used 3 months of recordings (January-March 2010) from the Socoa GNSS station to determine the tidal components in the GNSS-R signals and to identify the Xynthia storm
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Books on the topic "Continuous wavelet analysis"

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Führ, Hartmut. Abstract Harmonic Analysis of Continuous Wavelet Transforms. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b104912.

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Abstract Harmonic Analysis of Continuous Wavelet Transforms. Springer, 2005.

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Book chapters on the topic "Continuous wavelet analysis"

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Brackx, Fred, Nele De Schepper, and Frank Sommen. "Clifford-Jacobi Polynomials and the Associated Continuous Wavelet Transform in Euclidean Space." In Wavelet Analysis and Applications, 185–98. Basel: Birkhäuser Basel, 2006. http://dx.doi.org/10.1007/978-3-7643-7778-6_16.

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Han-zhang, Qu, Xu Chen, and Zhao Ruizhen. "An Application of Continuous Wavelet Transform in Differential Equations." In Wavelet Analysis and Its Applications, 107–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45333-4_15.

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Brackx, Fred, and Frank Sommen. "The Continuous Wavelet Transform in Clifford Analysis." In Clifford Analysis and Its Applications, 9–26. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-010-0862-4_2.

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Aubert, Hervé, and Dwight L. Jaggard. "Continuous Wavelet Transform Analysis of Fractal Superlattices." In Fractals, 245–59. London: Springer London, 1999. http://dx.doi.org/10.1007/978-1-4471-0873-3_16.

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Woraratsoontorn, P., and T. Leeudomwong. "Continuous Wavelet Transform Analysis of Heart Sounds." In Lecture Notes in Electrical Engineering, 745–52. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-84814-3_75.

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Ende, Marco, Alfred K. Louis, Peter Maass, and Gottfried Mayer-Kress. "EEG Signal Analysis by Continuous Wavelet Transform Techniques." In Nonlinear Analysis of Physiological Data, 213–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-71949-3_12.

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Aqil, Mounaim, and Atman Jbari. "Continuous Wavelet Analysis and Extraction of ECG Features." In Emerging Technologies in Biomedical Engineering and Sustainable TeleMedicine, 51–68. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-14647-4_5.

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Weisz, Ferenc. "Higher Dimensional Continuous Wavelet Transform in Wiener Amalgam Spaces." In Topics in Mathematical Analysis and Applications, 747–68. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06554-0_33.

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Handy, C., and R. Murenzi. "Continuous wavelet transform analysis of one-dimensional quantum ground states." In CRM Proceedings and Lecture Notes, 303–14. Providence, Rhode Island: American Mathematical Society, 1999. http://dx.doi.org/10.1090/crmp/018/24.

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Ikawa, Nobuko, Akira Morimoto, and Ryuichi Ashino. "Application of Complex Continuous Wavelet Analysis to Auditory Evoked Brain Responses." In Trends in Mathematics, 543–50. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04459-6_52.

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Conference papers on the topic "Continuous wavelet analysis"

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Brackx, F., H. De Schepper, N. De Schepper, F. Sommen, Theodore E. Simos, George Psihoyios, and Ch Tsitouras. "The generalized Hermitean Clifford-Hermite continuous wavelet transform." In Numerical Analysis and Applied Mathematics. AIP, 2007. http://dx.doi.org/10.1063/1.2790253.

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Masako Omachi and Shinichiro Omachi. "Fast calculation of continuous wavelet transform using polynomial." In 2007 International Conference on Wavelet Analysis and Pattern Recognition. IEEE, 2007. http://dx.doi.org/10.1109/icwapr.2007.4421725.

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Suni, Antti, Juraj Simko, and Martti Vainio. "Boundary detection using continuous wavelet analysis." In Speech Prosody 2016. ISCA, 2016. http://dx.doi.org/10.21437/speechprosody.2016-55.

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Bernstein, S. "Clifford Continuous Wavelet Transforms in Ll0,2 and Ll0,3." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS: International Conference on Numerical Analysis and Applied Mathematics 2008. American Institute of Physics, 2008. http://dx.doi.org/10.1063/1.2991006.

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Zegadi, Nacera, Francoise Peyrin, and Robert Goutte. "Continuous wavelet transform for oriented texture analysis." In Optical Science, Engineering and Instrumentation '97, edited by Akram Aldroubi, Andrew F. Laine, and Michael A. Unser. SPIE, 1997. http://dx.doi.org/10.1117/12.292806.

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Chang-Jiang Zhang, Chun-Jiang Duanmu, and Hui-Yu Chen. "Typhoon image segmentation by combining curvelet transform with continuous wavelet transform." In 2007 International Conference on Wavelet Analysis and Pattern Recognition. IEEE, 2007. http://dx.doi.org/10.1109/icwapr.2007.4421690.

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Bahri, Mawardi, and Ryuichi Ashimo. "Convolution and correlation theorems for continuous reduced biquaternion wavelet transform." In 2015 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR). IEEE, 2015. http://dx.doi.org/10.1109/icwapr.2015.7295930.

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Gang Wang, Bao-Qin Wang, and Yue-Xia Fu. "A study on the stability of g-continuous frames." In 2009 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR). IEEE, 2009. http://dx.doi.org/10.1109/icwapr.2009.5207495.

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Jaenisch, Holger M., James W. Handley, and Nathaniel Albritton. "Converting data into functions for continuous wavelet analysis." In SPIE Defense, Security, and Sensing, edited by Harold H. Szu and F. Jack Agee. SPIE, 2009. http://dx.doi.org/10.1117/12.817870.

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Bin Wu, Gang Liu, and Jun Guo. "Research on confusion network algorithm for Mandarin large vocabulary continuous speech recognition." In International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07. IEEE, 2007. http://dx.doi.org/10.1109/icwapr.2007.4421593.

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