Search results for "Wavelet analysi"
showing 10 items of 32 documents
An automated image analysis methodology for classifying megakaryocytes in chronic myeloproliferative disorders
2008
This work describes an automatic method for discrimination in microphotographs between normal and pathological human megakaryocytes and between two kinds of disorders of these cells. A segmentation procedure has been developed, mainly based on mathematical morphology and wavelet transform, to isolate the cells. The features of each megakaryocyte (e.g. area, perimeter and tortuosity of the cell and its nucleus, and shape complexity via elliptic Fourier transform) are used by a regression tree procedure applied twice: the first time to find the set of normal megakaryocytes and the second to distinguish between the pathologies. The output of our classifier has been compared to the interpretati…
Combining Haar Wavelet and Karhunen Loeve Transforms for Medical Images Watermarking
2014
This paper presents a novel watermarking method, applied to the medical imaging domain, used to embed the patient’s data into the corresponding image or set of images used for the diagnosis. The main objective behind the proposed technique is to perform the watermarking of the medical images in such a way that the three main attributes of the hidden information (i.e., imperceptibility, robustness, and integration rate) can be jointly ameliorated as much as possible. These attributes determine the effectiveness of the watermark, resistance to external attacks, and increase the integration rate. In order to improve the robustness, a combination of the characteristics of Discrete Wavelet and K…
Automated detection and localization system of myocardial infarction in single-beat ECG using Dual-Q TQWT and wavelet packet tensor decomposition.
2019
Abstract Background and objective It is challenging to conduct real-time identification of myocardial infarction (MI) due to artifact corruption and high dimensionality of multi-lead electrocardiogram (ECG). In the present study, we proposed an automated single-beat MI detection and localization system using dual-Q tunable Q-factor wavelet transformation (Dual-Q TQWT) denoising algorithm. Methods After denoising and segmentation of ECG, a fourth-order wavelet tensor (leads × subbands × samples × beats) was constructed based on the discrete wavelet packet transform (DWPT), to represent the features considering the information of inter-beat, intra-beat, inter-frequency, and inter-lead. To red…
Validation of a New Method for the Diagnosis of Rotor bar Failures via Wavelet Transformation in Industrial Induction Machines
2006
[EN] In this paper, the authors propose a method for the diagnosis of rotor bar failures in induction machines, based on the analysis of the stator current during the startup using the discrete wavelet transform (DWT). Unlike other approaches, the study of the high-order wavelet signals resulting from the decomposition is the core of the proposed method. After an introduction of the physical and mathematical bases of the method, a description of the proposed approach is given; for this purpose, a numerical model of induction machine is used in such a way that the effects of a bar breakage can clearly be shown, avoiding the influence of other phenomena not related with the fault. Afterward, …
The Use of the Wavelet Approximation Signal as a Tool for the Diagnosis of Rotor Bar Failures
2005
[EN] The aim of this paper is to present a new approach for rotor bar failure diagnosis in induction machines. The method focuses on the study of an approximation signal resulting from the wavelet decomposition of the startup stator current. The presence of the left sideband harmonic is used as evidence of the rotor failure in most diagnosis methods based on the analysis of the stator current. Thus, a detailed description of the evolution of the left sideband harmonic during the startup transient is given in this paper; for this purpose, a method for calculating the evolution of the left sideband during the startup is developed, and its results are physically explained. This paper also show…
A Mellin transform approach to wavelet analysis
2015
The paper proposes a fractional calculus approach to continuous wavelet analysis. Upon introducing a Mellin transform expression of the mother wavelet, it is shown that the wavelet transform of an arbitrary function f(t) can be given a fractional representation involving a suitable number of Riesz integrals of f(t), and corresponding fractional moments of the mother wavelet. This result serves as a basis for an original approach to wavelet analysis of linear systems under arbitrary excitations. In particular, using the proposed fractional representation for the wavelet transform of the excitation, it is found that the wavelet transform of the response can readily be computed by a Mellin tra…
Time-varying causality between crude oil and stock markets: What can we learn from a multiscale perspective?
2017
This paper investigates the presence of time-varying causal linkages in mean and variance between oil price changes and stock returns for six major oil-importing countries (France, Germany, Italy, Spain, the UK and the US) in a multiscale framework that combines wavelet analysis and a modified version of the dynamic causality test of Lu, Hong, Wang, Lai, and Liu (2014). The results show significant bidirectional causal relations between oil and stock markets at the different time horizons for all countries. The causal links tend to be stronger at coarser scales and in periods of financial turmoil, mainly during the recent global financial and European sovereign debt crises. This evidence pr…
Causal flows between oil and forex markets using high-frequency data: Asymmetries from good and bad volatility
2019
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. This paper investigates the causal linkages in volatility between crude oil prices and six major bilateral exchange rates against the U.S. dollar in the time-frequency space using high-frequency intraday data. Special attention is paid to the potential asymmetries in the causal effects between oil and forex markets. The wavelet-based Granger causality method proposed by Olayeni (2016) is applied to quantify the causal relations in the time and frequency domains simultaneously. Moreover, the realized semivariance approach of Barndoff-Nielsen et a…
An approach based on wavelet analysis for feature extraction in the electroretinogram
2011
Most biomedical signals are non-stationary. The knowledge of their frequency content and temporal distribution is then useful in a clinical context. The wavelet analysis is appropriate to achieve this task. The present paper uses this method to reveal hidden characteristics and anomalies of the human a-wave, an important component of the electroretinogram since it is a measure of the functional integrity of the photoreceptors. We here analyse the time–frequency features of the a-wave both in normal subjects and in patients affected by Achromatopsia, a pathology disturbing the functionality of the cones. The results indicate the presence of two or three stable frequencies that, in the pathol…
Vibration signature analysis for rotor broken bar diagnosis in double cage induction motor drives
2013
The paper investigates the diagnosis of rotor broken bars in field oriented controlled (FOC) double cage induction motor drives, using current and vibration signature analysis techniques. The Impact of the closed loop control system cannot be neglected when the detection of asymmetries in the machine are based on the signature analysis of electrical variables. The proposed diagnosis approach is based on optimized use of wavelet analysis by a pre-processing of phase current or axial/radial vibration signals. Thus, the time evolution of the tracked rotor fault components can be effectively analyzed. This paper shows also the relevance of the fault components computed from axial vibration sign…