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Gotowe bibliografie tematyczne / ENSEMBLE EMPIRIAL MODE DECOMPOSITION

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Gotowa bibliografia na temat „ENSEMBLE EMPIRIAL MODE DECOMPOSITION”

Autor: Grafiati

Data publikacji: 11 września 2023

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Rozprawy doktorskie na temat "ENSEMBLE EMPIRIAL MODE DECOMPOSITION"

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Furlaneto, Dennis Carnelossi. "An analysis of ensemble empirical mode decomposition applied to trend prediction on financial time series." reponame:Repositório Institucional da UFPR, 2017. http://hdl.handle.net/1884/49137.

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Orientador : Luiz Eduardo S. Oliveira<br>Coorientador : David Menotti<br>Dissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa: Curitiba, 20/07/2017<br>Inclui referências : f. 63-72<br>Resumo: As séries temporais financeiras são notoriamente difíceis de analisar e prever dada sua natureza não estacionária e altamente oscilatória. Nesta tese, a eficácia da técnica de decomposição não-paramétrica Ensemble Empirical Mode Decomposition (EEMD) é avaliada como uma técnica de extração de característica de séries temporais p

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Li, Zhendan. "An Ensemble Empirical Mode Decomposition Approach to Wear Particle Detection in Lubricating Oil Subject to Particle Overlap." Thèse, Université d'Ottawa / University of Ottawa, 2011. http://hdl.handle.net/10393/20313.

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With the development of mechanical fault diagnosis technology, complex mechanical systems do not need to be shut down periodically for the maintenance. The working condition of the mechanical systems can be monitored by analyzing the wear metal particles in the systems' lubricating oil. However, the output signals of the monitoring sensor are non-stationary. In some case the particle signals are overlapped with each other. The goal of this thesis is to find a method to decompose those overlapped particle signals, and then count the particle number in the lubricating oil. At the beginning EMD

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Alshahrani, Saeed Sultan. "Detection, classification and control of power quality disturbances based on complementary ensemble empirical mode decomposition and artificial neural networks." Thesis, Brunel University, 2017. http://bura.brunel.ac.uk/handle/2438/15872.

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Lozano, García Manuel. "Multichannel analysis of normal and continuous adventitious respiratory sounds for the assessment of pulmonary function in respiratory diseases." Doctoral thesis, Universitat Politècnica de Catalunya, 2015. http://hdl.handle.net/10803/397706.

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Respiratory sounds (RS) are produced by turbulent airflows through the airways and are inhomogeneously transmitted through different media to the chest surface, where they can be recorded in a non-invasive way. Due to their mechanical nature and airflow dependence, RS are affected by respiratory diseases that alter the mechanical properties of the respiratory system. Therefore, RS provide useful clinical information about the respiratory system structure and functioning. Recent advances in sensors and signal processing techniques have made RS analysis a more objective and sensitive tool

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Quinlan, John Mathew. "Investigation of driving mechanisms of combustion instabilities in liquid rocket engines via the dynamic mode decomposition." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54343.

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Combustion instability due to feedback coupling between unsteady heat release and natural acoustic modes can cause catastrophic failure in liquid rocket engines and to predict and prevent these instabilities the mechanisms that drive them must be further elucidated. With this goal in mind, the objective of this thesis was to develop techniques that improve the understanding of the specific underlying physical processes involved in these driving mechanisms. In particular, this work sought to develop a small-scale, optically accessible liquid rocket engine simulator and to apply modern, high-s

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Wei, Shao-Kuan, and 魏韶寬. "Ensemble Empirical Mode Decomposition with Clustering Analysis." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/82011189687957252619.

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碩士<br>國立臺灣師範大學<br>數學系<br>100<br>Ensemble Empirical Mode Decomposition (EEMD) is an adaptive time-frequency data analysis method. Time series or signals can be decomposed into a collection of intrinsic mode functions (IMFs). Nevertheless, there appears a multi-mode problem where signals with a similar time scale are decomposed into different IMFs. A possible solution to this problem is to combine the multi-modes into a proper single mode, but there is no general rule on how to combine IMFs in the literature. In this paper, we propose to modify EEMD algorithm using the statistical clustering an

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Sheng-MaoWang and 王晟懋. "Automated program of Ensemble Empirical Mode Decomposition." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/2yg4c2.

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碩士<br>國立成功大學<br>航空太空工程學系<br>107<br>The ensemble empirical mode decomposition (EEMD) method is applied for wind data analysis in the current research. However, calculations could take a very long time. Therefore, an attempt is made to accelerate the calculations. MATLAB and Python are used to explore the characteristics of different programming language operations, and a user-friendly graphical interface is also developed, and the execution process will be operated automatically and continuously. The wind data analyzed were collected by the wind turbines located on campus of Case Western R

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Yang, Sheng-Ning, and 楊勝寧. "Using Complementary Ensemble Empirical Mode Decomposition Method To Analyze Images." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/38533054079787149646.

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碩士<br>國立陽明大學<br>醫學工程研究所<br>99<br>In this study, by Huang NE, who proposed the complementary empirical mode decomposition method based on the empirical mode decomposition method. The algorithm inherits the empirical mode decomposition some of the benefits. For example it can solve nonlinear and nonstationary signals. Another Empirical mode decomposition method and the traditional numerical methods, the base need to know prior to analysis, the original signals can be based on the characteristics and nature of the original signal automatically a number of nature apart from the function and the re

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Chen-KuoChen and 陳振國. "The Study of Pile Integrity Test Using Ensemble Empirical Mode Decomposition." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/55168835560927508888.

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碩士<br>國立成功大學<br>土木工程學系<br>105<br>Non-destructive testing (NDT) has the advantages of economical, fast, and a wide range of applicability. Therefore it is a fairly effective testing method. The testing of piles without pile cap has been considered a well-developed technique. However, affected by complex boundaries conditions, testing of piles with pile cap is more difficult. This study use Impulse response (IR) method for the field test, then use ensemble empirical mode decomposition (EEMD) by Hilbert-Huang Transform to decompose the signals, finally use Fast Fourier Transform (FFT) to transfor

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Tsai, Shu-Yun, and 蔡舒韻. "A Novel Energy Detection Method Based on Ensemble Empirical Mode Decomposition." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/mu66ak.

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碩士<br>國立東華大學<br>電機工程學系<br>100<br>Cognitive radio(CR) is a novel smart wireless communication technology. To improve spectrum utilization efficiency, CR can detect the communication environment features to automatically adjust the transmitting and receiving parameters of a system, such as power, frequency, and modulation mode etc. The spectrum sensing is a key technology in the CR. In this thesis, we use energy detection for spectrum sensing. Many researches on energy detection are performed on the basis of a precise knowledge of noise power environment to set threshold. In this thesis we use e

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