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.
Results
Showing 1 to 20 of 36 for “"Empirical mode decomposition"”.
-
Multidimensional and multivariate empirical mode decomposition
Over the last decade, Empirical Mode Decomposition (EMD) has developed into a versatile tool for adaptive, scale-based modal decomposition. EMD has proven to be capable of decomposing multivariate signals with cross-channel mode alignment. However, the algorithms for envelope identification in …
-
MID-ATLANTIC RIDGE (12~16oN) BATHYMETRIC ANALYSIS BY EMPIRICAL MODE DECOMPOSITION
… on previous studies. This study applies 2-D Empirical Mode Decomposition (EMD) to simulate a similar 1D global study of mid-ocean ridges by Small (1994; 1998), but with fewer than 10 intrinsic mode functions (IMFs). With appropriate combination of IMFs, this study acquires not only similar …
-
An Integrated Compensation System Based on Empirical Mode Decomposition for Robust Noninvasive Blood Pressure Estimation
… are suppressed using algorithms based on Empirical Mode Decomposition (EMD), which has the feature of removing unwanted noise components little effect on the phase or the frequency distribution of the measured signal. With motion artifacts, measurements show that the proposed algorithms …
-
Empirical mode decomposition applied to planar and volumetric velocity field measurements of a supersonic separated flow
… extensions of fast and adaptive empirical mode decomposition (FAEMD) are implemented on both three-component planar and volumetric velocity fields of a Mach 2.5 supersonic base flow which were obtained using particle image velocimetry. The resulting two-dimensional intrinsic mode …
-
Damage Detection and System Identification using a Wavelet Energy Based Approach
… the physical parameters of an analytical model. First, the connection coefficients for the scaling function were developed for deriving the responses of the velocity and displacement from the acceleration responses. Next, defining the dominant sets based on the relative energies of the …
-
Data-driven system identification of strongly nonlinear modal interactions and model updating of nonlinear dynamical systems
… the calibration and validation of computational models. When a model fails to reproduce measurements, engineers must identify and incorporate the unmodeled and/or uncertain dynamics to reconcile theoretical prediction and experimental observation. While linear identification tools are …
-
Towards Multiclass Damage Detection and Localization using Limited Vibration Measurements
… response). Over the last few decades, various model-based and time-frequency methods have shown great promises for damage identification and localization. However, the existing methods are unable to perform satisfactorily in many situations, including the presence of limited sensor measurements …
-
Long Term Ground Based Precipitation Data Analysis: Spatial and Temporal Variability
… response variables (classifiers) on various models applied to the detection of El Niño Southern Oscillation (ENSO) on California’s seven climate divisions by using modeled and gauge (in-situ/ground) precipitation measurements and various climate indices. Three scientific studies were …
-
An evaluation of noise reduction algorithms for particle-based fluid simulations in multi-scale applications
… A significant drawback of nano- or micro-scale modelling is the substantial noise associated with particle techniques, which disturbs the analysis of the results. The uncertainty in the mean of the ensemble is due to fluctuations caused e.g. by additional forcing terms (thermostats). Extracting …
-
Three essays on the UK Electricity Market: Risk Premium,Uncertainty of Supply and Forecasting
… for the uncertainty of renewable supply. The empirical results suggest that the UK electricity forward market provides risk premia, which is higher for electricity generated from renewable sources as a compensation for the uncertainty of renewable supply. Secondly, the role of imbalances …
-
Electrocardiogram-based detection of heart pathologies using nonlinear methods and machine learning
… και μέτρων αποσύνθεσης εμπειρικών τρόπων (empirical mode decomposition). Τα χαρακτηριστικά αξιολογήθηκαν με πολλαπλούς ταξινομητές, με έμφαση στην απόδοση ανά κατηγορία και στην ερμηνευσιμότητα των χαρακτηριστικών σε επίπεδο απαγωγής (lead) και παθολογίας. Για την αντιμετώπιση της …
-
Machine Learning-Driven Corrosion Detection and Classification in Pipelines
… was processed using the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Bhattacharyya Variance Distance (BVD) algorithms to enhance signal quality. Key features indicative of pipeline condition were extracted and subjected to clustering analysis using the …
-
Analysis and techniques of partial shading detection and classification in solar photovoltaic arrays
… Wavelet Packet Transform (WPT) along with Empirical Mode Decomposition (EMD) to extract the features of PV panel output voltage and string current signals during partial shading conditions. In the first stage, the WPT is used to split the PV voltage and string currents into specific …
-
Feature extraction and data reduction for hyperspectral remote sensing Earth observation
… from vector to matrix arrays. Inspired by Empirical Mode Decomposition (EMD) methods, a recent and promising algorithm, Singular Spectrum Analysis (SSA), is introduced to hyperspectral remote sensing, performing extraction of features in the spectral (1D-SSA) and also the spatial (2D-SSA) …
-
Time-frequency domain analysis of exchange rate market integration in Southern Africa Development Community: A Hilbert-Huang Transform approach
… non-stationarity and non-linearity influence the modelling of such data in terms of the accuracy of the analysis and the embedded policy direction. In response, this thesis proposes empirical mode decomposition-based market integration analysis to address the limitations of the existing literature …
-
Construction of frequency-energy plots for nonlinear dynamical systems from time-series data
… stiffnesses present in a system. Separately, the empirical mode decomposition (EMD) method is used to decompose the system response into intrinsic mode functions (IMFs) whose frequencies are then estimated with the Hilbert transform. The FEP is created by plotting these estimated frequencies …
-
Head Position Variability During Single and Dual-task Tandem Gait Concussion Testing Protocol
… and center of pressure (COP), filtered using empirical mode decomposition, were measured during the tasks and analyzed by the 1st pass (FP), turn (T), and 2nd (SP) using a custom MATLAB code. The time to complete the task and average mean excursion in the ML direction, velocity in the ML …
-
Hypernasal Speech Analysis via Emperical Mode Decomposition and the Teager-Kasiser Energy Operator
… analysis methods of using a linear source model follow the premise that differences between normal and hypernasal speech can be distinguished by shifts or power changes in the formant frequencies and/or the widening (or narrowing) of the formant bandwidths. Such a premise, however, has not …
-
Partial discharge denoising for power cables
… it presents new findings in the application of empirical mode decomposition (EMD) in PD denoising. Wavelet-based technique has received high attention in the area of PD denoising, it still faces challenges, however, in wavelet selection, decomposition scale determination, and noise estimation. …
Page 1 of 2