Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 24 for “"Wavelet Decomposition"”.
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A spatial scalable video coding with selective data transmission using wavelet decomposition.
… to achieve this scalable framework we have used wavelets, for greater flexibility, and a multiresolution approach. The multiresolution motion estimation (MRME) provides the reusability of motion vectors across different resolution levels. In MRME the motion estimation, which is carried out in the …
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Detection of breast cancer microcalcifications in digitized mammograms. Developing segmentation and classification techniques for the processing of MIAS database mammograms based on the Wavelet Decomposition Transform and Support Vector Machines
… help in identifying regions of interest. The wavelet transform has been utilized for this process as it provides a variety of features that could be examined in future studies. The third and final stage is classification, where machine learning is applied to be able to distinguish between …
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Detection of breast cancer microcalcifications in digitized mammograms. Developing segmentation and classification techniques for the processing of MIAS database mammograms based on the Wavelet Decomposition Transform and Support Vector Machines.
… help in identifying regions of interest. The wavelet transform has been utilized for this process as it provides a variety of features that could be examined in future studies. The third and final stage is classification, where machine learning is applied to be able to distinguish between …
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Automated detection of breast cancer using SAXS data and wavelet features
… techniques as a semi-automatic screen. Wavelet based features were generated from the SAXS image data. The features were supplied to a classifier, which sorted the images into distinct groups, such as “normal” and “tumor”. The main problem in the project was to find a set of features …
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MEAN REVERSION MODELING WITH APPLICATION IN ENERGY MARKETS
… patterns of energy assets: Time-invariant Wavelet-Schwartz Model and Time-Varying State Space Model. The first model is capable of describing stationary time series with fixed degree of mean-reversion by incorporating wavelet-decomposition techniques into the one-factor Schwartz model. As a …
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Support vector machine and parametric wavelet-based texture classification of stem cell images
… texture by the subband energies of the image's wavelet decomposition, and we employ a non-parametric support vector machine to perform the classification that yields the segmentation. We also adapt a parametric wavelet-based classifier that utilizes the Kullback-Leibler distance. We apply both …
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Multiresolution wavelet analysis of event-related EEG potentials using ensemble of classifier data fusion techniques for early diagnosis of Alzheimer's disease
… signals is accomplished through multiresolution wavelet decomposition, producing time-frequency features in successive spectral bands. In previous studies, these feature sets were concatenated and used as inputs to a neural network classifier. This contribution investigates training an ensemble …
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A Novel Approach for Continuous Speech Tracking and Dynamic Time Warping. Adaptive Framing Based Continuous Speech Similarity Measure and Dynamic Time Warping using Kalman Filter and Dynamic State Model
… spotting approach is proposed by introducing wavelet decomposition based dynamic noise filter and combination of beliefs. The Dempster’s theory of belief combination is deployed for the first time in relation to keyword spotting task. Performances for both; speech tracking and keyword spotting …
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Multi-resolution dental image registration based on genetic algorithm
… techniques namely image sub sampling and wavelet decomposition. Multi resolution techniques help in the reduction of search data since initial registration is carried at lower levels and results are updated as the levels of resolutions increase. We adopted edges as image features that …
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Three essays on the UK Electricity Market: Risk Premium,Uncertainty of Supply and Forecasting
… estimation methods, such as frequency filters, wavelet decomposition, empirical mode decomposition and hodrick–prescott (HP) filter according to the Diebold and Mariano (1995) test.
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Defect Detection in Selective Laser Melting
… signal amplitude, Fourier Transform, and Wavelet Decomposition.</p> <p>The developed print parameters reduced warpage in the part by better distributing heat throughout the build envelope. Reducing warpage enabled the lower portion of the part to be printed intact, preserving it to …
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Patient-specific seizure onset detection
… from a single patient. We use a multi-level wavelet decomposition to extract features that capture the amplitude, fundamental frequency, and morphology of EEG waveforms. These features are then classified using a support vector machine or maximum-likelihood classifier trained on a patient's …
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Measurement and analysis of breath sounds
… procedures has been investigated. Based on wavelet decomposition and selective synthesis, heart sounds can be reduced with a cost of unnatural breath sounds. Heart sound reduction is shown not to be necessary if a time-frequency representation is used, as heart sounds have a fixed pattern in …
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Structural Health Monitoring Using Multiple Piezoelectric Sensors and Actuators
… often used in ultrasonic testing, together with wavelet decomposition to extract traveling pulses from a noisy signal. The results for a one-dimensional structure show that we can determine the damage location to within a spatial resolution determined by the temporal resolution of the data …
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Multidimensional Wavelets and Neural Networks
The construction of scaling functions and wavelets in multiple dimensions and for arbitrary scaling matrices is a challenging task entailing some complexities. Existing approaches mainly focus on the two-dimensional case using dyadic or quincunx sampling. This thesis aims to develop a method to …
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Improvement of Geometric Quality Inspection and Process Efficiency in Additive Manufacturing
… alignment and inspection framework based on wavelet decomposition and design of experiments (DOE). The new framework is able to improve the alignment accuracy and to distinguish different sources of error based on the shape deviation of each layer. In addition, a quickest change point …
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Multiscale techniques for image segmentation, classification and retrieval
… Tree. This framework is based on the complex wavelet decomposition of a given image. The unsupervised Mean Shift Procedure is used to determine the number of object classes. Most unsupervised techniques are difficult to evaluate due to a lack of ground data on which evaluation of performance …
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Automated wavelet-based fault detection and diagnosis for smart distribution systems and microgrids
… until now. In this thesis, an automated wavelet-based fault detection and diagnosis technique based on a combination of Wavelet Transform, Harmony Search Algorithm, and Machine Learning approaches is developed for fault diagnosing in the Micro-Grid systems. The harmony search algorithm as …
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Classification of multiwavelength transients with machine learning
… grid using Gaussian processes, we then perform a wavelet decomposition and finally reduce the dimensionality using principal component analysis. We then classify the light curves with the popular machine learning algorithm random forests. For the first time, we apply machine learning to the …
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Experimental and numerical investigations on wind characteristics and wind induced vibrations of bridge structures
… a more accurate prediction method based on wavelet decomposition and chaotic diagnosis is also proposed. The wind speed prediction method considers the frequency domain characteristics of wind speed series for improving prediction accuracy. Wind speed data collected from the long term …
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