Search results for "Continuous wavelet"

showing 10 items of 27 documents

Wavelet and fractal approach to surface roughness characterization after finish turning of different workpiece materials

2009

In this paper, the surface profiles generated in longitudinal turning operations were characterized using continuous wavelet transform (CWT) and normalized fractal dimension Dn. In the comparative analysis, some characteristic roughness profiles after the turning of different workpiece materials, such as C45 medium carbon steel, nodular cast iron and hardened (55 HRC) high-strength alloy steel were selected. For wavelet characterization, both Morlet and ‘Mexican hat’ analyzing wavelets, which allow the assessment of extrema and frequency distribution, were utilized. The results of the CWT as a function of profile and momentary wavelet length are presented. It is concluded that CWT can be us…

Materials scienceAcousticsAlloy steelMetallurgyMetals and AlloysWavelet transformSurface finishengineering.materialFractal dimensionIndustrial and Manufacturing EngineeringComputer Science ApplicationsFractalWaveletModeling and SimulationCeramics and CompositesengineeringSurface roughnessContinuous wavelet transformJournal of Materials Processing Technology
researchProduct

Time-Frequency behaviour of the a-wave of the human electroretinogram

2007

The electroretinogram is the record of the electrical response of the retina to a light stimulus. The two main components are the a-wave and the b-wave, the former is related to the early photoreceptoral activity. Aim of this paper is to acquire useful information about the time-frequency features of the human a-wave, by means of the wavelet analysis. This represents a proper approach in dealing with nonstationary signals. We have used the Mexican Hat as mother wavelet. The analysis, carried out for four representative values of the luminance, comprehends the frequency dependence of the variance and the skeleton. The results indicate a predominance of low frequency components, their time di…

Waveletbusiness.industryTime distributionPattern recognitionArtificial intelligenceFrequency dependenceStimulus (physiology)Low frequencybusinessLuminanceContinuous wavelet transformMathematicsTime–frequency analysis
researchProduct

Two-dimensional wavelet transform by wavelength multiplexing

1996

The wavelet transform is a useful tool for data compression, analysis of short transient pulses, optical correlators, etc. This transform was obtained optically by the use of the spatial or temporal multiplexing approaches. A two-dimensional wavelet transform is obtained with only one spatial channel. The information of the different scalings is carried in different wavelengths and summed incoherently at the output plane. Laboratory experimental results are demonstrated.

Discrete wavelet transformPhysicsbusiness.industryMaterials Science (miscellaneous)Wavelet transformIndustrial and Manufacturing EngineeringWavelet packet decompositionOpticsWaveletBusiness and International ManagementbusinessHarmonic wavelet transformFast wavelet transformContinuous wavelet transformConstant Q transformApplied Optics
researchProduct

Estimation of Muscular Fatigue under Electromyostimulation Using CWT

2012

International audience; The aims of this study are to investigate muscular fatigue and to propose a new fatigue index based on the continuous wavelet transform (CWT) which is compared to the standard fatigue indexes from literature. Fatigue indexes are all based on the electrical activity of muscles (electromyogram) acquired during an electrically stimulated contraction thanks to two modules (electromyostimulation + electromyography recording) that can analyze EMG signals in real time during electromyostimulation. The extracted parameters are compared with each other and their sensitivity to noise is studied. The effect of truncation of M waves is then investigated, enlightening the robustn…

AdultMaletruncationwavelet.Acoustics0206 medical engineeringBiomedical EngineeringWavelet Analysis02 engineering and technologyElectromyography03 medical and health sciences0302 clinical medicineWaveletwaveletmedicineHumansContinuous wavelet transformMathematicsMuscle fatiguemedicine.diagnostic_testMuscle fatigueElectromyographyBiomechanicsWavelet transform020601 biomedical engineering[SPI.TRON] Engineering Sciences [physics]/ElectronicsElectric StimulationElectromyogram[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsForearmMuscular fatigueArmElectromyostimulation030217 neurology & neurosurgeryBiomedical engineering
researchProduct

Multi axis representation and Euclidean distance of muscle fatigue indexes during evoked contractions

2014

International audience; In this article, we proposed a new representation of muscular fatigue during evoked muscle contractions based on fatigue indexes such as peak to peak amplitude, RMS of the M wave, mean and median frequency and fatigue index calculated from continuous wavelet transform (I CWT). These new representations of muscle fatigue using multi axis represented and Euclidean distance give better insights on changes in physiological characteristics during muscle fatigue. This technique provides a fatigue index using several muscle characteristics. The use of other kinds of fatigue characteristics as force could also be possible.

medicine.diagnostic_testMuscle fatigueSpeech recognitionMulti axis0206 medical engineeringMathematical analysis02 engineering and technologyElectromyography[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing020601 biomedical engineering[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsEuclidean distance03 medical and health sciences0302 clinical medicineAmplitudeMuscular fatiguemedicineRepresentation (mathematics)[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing030217 neurology & neurosurgeryContinuous wavelet transform[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingMathematics
researchProduct

Effect of parametric variation of center frequency and bandwidth of morlet wavelet transform on time-frequency analysis of event-related potentials

2017

Time-frequency (TF) analysis of event-related potentials (ERPs) using Complex Morlet Wavelet Transform has been widely applied in cognitive neuroscience research. It has been widely suggested that the center frequency (fc) and bandwidth (σ) should be considered in defining the mother wavelet. However, the issue how parametric variation of fc and σ of Morlet wavelet transform exerts influence on ERPs time-frequency results has not been extensively discussed in previous research. The current study, through adopting the method of Complex Morlet Continuous Wavelet Transform (CMCWT), aims to investigate whether time-frequency results vary with different parametric settings of fc and σ. Besides, …

Discrete wavelet transformcomplex morlet wavelet transformbandwidthbusiness.industrySpeech recognitionPattern recognitionevent-related potentialsWavelet packet decompositioncenter frequencyWaveletTime–frequency representationMorlet wavelettime-frequency representationArtificial intelligencebusinessContinuous wavelet transformConstant Q transformMathematicsParametric statistics
researchProduct

One and Two Dimensional Convolutional Neural Networks for Seizure Detection Using EEG Signals

2021

Deep learning for the automated detection of epileptic seizures has received much attention during recent years. In this work, one dimensional convolutional neural network (1D-CNN) and two dimensional convolutional neural network (2D-CNN) are simultaneously used on electroencephalogram (EEG) data for seizure detection. Firstly, using sliding windows without overlap on raw EEG to obtain the definite one-dimension time EEG segments (1D-T), and continuous wavelet transform (CWT) for 1D-T signals to obtain the two-dimension time-frequency representations (2D-TF). Then, 1D-CNN and 2D-CNN model architectures are used on 1D-T and 2D-TF signals for automatic classification, respectively. Finally, t…

convolutional neural networks (CNN)Computer scienceseizure detection02 engineering and technologyneuroverkotElectroencephalographyConvolutional neural network0202 electrical engineering electronic engineering information engineeringmedicineEEGContinuous wavelet transformSignal processingArtificial neural networkmedicine.diagnostic_testbusiness.industryelectroencephalogram (EEG)signaalinkäsittelyDeep learningtime-frequency representationtideep learningsignaalianalyysi020206 networking & telecommunicationsPattern recognitionkoneoppiminenBenchmark (computing)020201 artificial intelligence & image processingArtificial intelligencebusinessepilepsia
researchProduct

The Wavelet Scalogram in the Study of Time Series

2014

Wavelet theory has been proved to be a useful tool in the study of time series. Specifically, the scalogram allows the detection of the most representative scales (or frequencies) of a signal. In this work, we present the scalogram as a tool for studying some aspects of a given signal. Firstly, we introduce a parameter called scale index, interpreted as a measure of the degree of the signal’s non-periodicity. In this way, it can complement the maximal Lyapunov exponent method for determining chaos transitions of a given dynamical system. Secondly, we introduce a method for comparing different scalograms. This can be applied for determining if two time series follow similar patterns.

Discrete wavelet transformsymbols.namesakeWaveletSeries (mathematics)Computer sciencesymbolsLyapunov exponentDynamical systemAlgorithmMeasure (mathematics)Continuous wavelet transformComplement (set theory)
researchProduct

Locally Supported Wavelets on Manifolds with Applications to the 2D Sphere

1999

Abstract In this paper we present a construction principle for locally supported wavelets on manifolds once a multiresolution analysis is given. The wavelets provide a stable (or unconditional) basis for a scale of Sobolev spaces H s , 0 ≤ s ≤ s . We examine a fast wavelet transform with almost optimal complexity. For the two-dimensional sphere we construct a multiresolution analysis generated by continuous splines that are bilinear with respect to some special spherical grid. In our approach the poles are not exceptional points concerning the approximation power or the stability of the wavelet basis. Finally we present some numerical applications to singularity detection and the analysis o…

Sobolev spaceDiscrete wavelet transformWaveletSingularityLegendre waveletMultiresolution analysisApplied MathematicsMathematical analysisFast wavelet transformContinuous wavelet transformMathematicsApplied and Computational Harmonic Analysis
researchProduct

A wavelet-based tool for studying non-periodicity

2010

This paper presents a new numerical approach to the study of non-periodicity in signals, which can complement the maximal Lyapunov exponent method for determining chaos transitions of a given dynamical system. The proposed technique is based on the continuous wavelet transform and the wavelet multiresolution analysis. A new parameter, the \textit{scale index}, is introduced and interpreted as a measure of the degree of the signal's non-periodicity. This methodology is successfully applied to three classical dynamical systems: the Bonhoeffer-van der Pol oscillator, the logistic map, and the Henon map.

Dynamical systems theoryFOS: Physical sciencesLyapunov exponentDynamical Systems (math.DS)37D99 42C40WaveletsDynamical systemMeasure (mathematics)symbols.namesakeWaveletModelling and SimulationFOS: MathematicsApplied mathematicsMathematics - Dynamical SystemsContinuous wavelet transformMathematicsMathematical analysisNonlinear Sciences - Chaotic DynamicsNon-periodicityHénon mapNonlinear Sciences::Chaotic DynamicsComputational MathematicsComputational Theory and MathematicsModeling and SimulationsymbolsLogistic mapChaotic Dynamics (nlin.CD)Chaotic dynamical systems
researchProduct