Relevant bibliographies by topics / Emperical Mode Decomposition (EMD)

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Emperical Mode Decomposition (EMD)'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Emperical Mode Decomposition (EMD)"

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Pradika, Eky Fortuna, Achmad Widodo, and Ismoyo Haryanto. "Diagnosis Kerusakan Roda Gigi dengan Metode Ensemble Emperical Mode Decomposition (EEMD)." ROTASI 20, no. 4 (2019): 207. http://dx.doi.org/10.14710/rotasi.20.4.207-213.

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Perawatan mesin merupakan suatu kombinasi dari berbagai tindakan yang dilakukan untuk menjaga performa mesin atau memperbaikinya sampai pada suatu kondisi yang bisa diterima. Dalam dunia industri, pemeliharaan memberikan pengaruh yang sangat besar bagi kondisi mesin dan jumlah produksi. Penggunaan mesin dalam jangka waktu lama tentunya akan membutuhkan perawatan, salah satu metode perawatan adalah perawatan prediktif. Roda gigi adalah komponen yang sangat penting pada mesin, oleh karenanya roda gigi juga perlu diperhatikan kondisinya untuk menghindari kerusakan pada saat pengoperasian mesin. M
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Lv, Zhong Liang, Yi Lin Liu, Xian Wu Han, and Min Liu. "Study on Rolling Element Bearing Fault Diagnosis Methods Based on Ensemble Empirical Mode Decomposition." Applied Mechanics and Materials 457-458 (October 2013): 602–7. http://dx.doi.org/10.4028/www.scientific.net/amm.457-458.602.

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For rotating machinery, a fault diagnosis method is proposed on the basis of the EEMD (Ensemle Emperical Mode Decomposition) and Correlation Coefficient Method. In the Vibration Signals and rotate speed of rotating machinery, the fault diagnosis method is achieved by Spectrum Analysis and real-time monitoring. The original signals are decomposed into several IMF components. Each IMF contains the local feature of the signal. Correlation coefficient method is used to select the appropriate Intrinsic Mode Function. Extract the fault feature through its envelope diagram. Experiment proves the feas
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Eman, Alharbi, Rasheed Saim, and Buhari Seyed. "BRAIN Journal - Single Trial Classification of Evoked EEG Signals Due to RGB Colors." BRAIN - Broad Research in Artificial Intelligence and Neuroscience 7, no. 1 (2016): 29–41. https://doi.org/10.5281/zenodo.1044255.

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ABSTRACT Recently, the impact of colors on the brain signals has become one of the leading researches in BCI systems. These researches are based on studying the brain behavior after color stimulus, and finding a way to classify its signals offline without considering the real time. Moving to the next step, we present a single trial classification model for EEG signals evoked by RGB colors stimuli, which is not presented in previous studies. In this research, EEG signals were recorded from 7 subjects through BCI2000 toolbox. The Empirical Mode Decomposition (EMD) technique was used at the signa
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Safie, S. I., and Rahim Rosuhana. "Quality assessment on muscle locations for speech representation." Indonesian Journal of Electrical Engineering and Computer Science (IJEECS) 17, no. 2 (2020): 957–67. https://doi.org/10.11591/ijeecs.v17.i2.pp957-967.

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There are more than 68 muscles, which are activated either simultaneously or sequentially during speech production. To monitor the signals from all these muscles at once, involve a lot of sensors and such system is very expensive. In the Quran therapeutic treatment applications, the use of specific muscles is very important, for the production of correct Arabic pronunciation. The proper pronunciation will improve the reader's understanding of what is being read, thus assisting the effectiveness of the therapy process. The objective of this study is to identify the most optimal muscle locat
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TSUI, PO-HSIANG, CHIEN-CHENG CHANG, and NORDEN E. HUANG. "NOISE-MODULATED EMPIRICAL MODE DECOMPOSITION." Advances in Adaptive Data Analysis 02, no. 01 (2010): 25–37. http://dx.doi.org/10.1142/s1793536910000410.

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The empirical mode decomposition (EMD) is the core of the Hilbert–Huang transform (HHT). In HHT, the EMD is responsible for decomposing a signal into intrinsic mode functions (IMFs) for calculating the instantaneous frequency and eventually the Hilbert spectrum. The EMD method as originally proposed, however, has an annoying mode mixing problem caused by the signal intermittency, making the physical interpretation of each IMF component unclear. To resolve this problem, the ensemble EMD (EEMD) was subsequently developed. Unlike the conventional EMD, the EEMD defines the true IMF components as t
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NIAZY, R. K., C. F. BECKMANN, J. M. BRADY, and S. M. SMITH. "PERFORMANCE EVALUATION OF ENSEMBLE EMPIRICAL MODE DECOMPOSITION." Advances in Adaptive Data Analysis 01, no. 02 (2009): 231–42. http://dx.doi.org/10.1142/s1793536909000102.

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Empirical mode decomposition (EMD) is an adaptive, data-driven algorithm that decomposes any time series into its intrinsic modes of oscillation, which can then be used in the calculation of the instantaneous phase and frequency. Ensemble EMD (EEMD), where the final EMD is estimated by averaging numerous EMD runs with the addition of noise, was an advancement introduced by Wu and Huang (2008) to try increasing the robustness of EMD and alleviate some of the common problems of EMD such as mode mixing. In this work, we test the performance of EEMD as opposed to normal EMD, with emphasis on the e
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Chen, Zhongzhe, Baqiao Liu, Xiaogang Yan, and Hongquan Yang. "An Improved Signal Processing Approach Based on Analysis Mode Decomposition and Empirical Mode Decomposition." Energies 12, no. 16 (2019): 3077. http://dx.doi.org/10.3390/en12163077.

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Empirical mode decomposition (EMD) is a widely used adaptive signal processing method, which has shown some shortcomings in engineering practice, such as sifting stop criteria of intrinsic mode function (IMF), mode mixing and end effect. In this paper, an improved sifting stop criterion based on the valid data segment is proposed, and is compared with the traditional one. Results show that the new sifting stop criterion avoids the influence of end effects and improves the correctness of the EMD. In addition, a novel AEMD method combining the analysis mode decomposition (AMD) and EMD is develop
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XIE, QIWEI, BO XUAN, SILONG PENG, JIANPING LI, WEIXUAN XU, and HUA HAN. "BANDWIDTH EMPIRICAL MODE DECOMPOSITION AND ITS APPLICATION." International Journal of Wavelets, Multiresolution and Information Processing 06, no. 06 (2008): 777–98. http://dx.doi.org/10.1142/s0219691308002689.

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There are some methods to decompose a signal into different components such as: Fourier decomposition and wavelet decomposition. But they have limitations in some aspects. Recently, there is a new signal decomposition algorithm called the Empirical Mode Decomposition (EMD) Algorithm which provides a powerful tool for adaptive multiscale analysis of nonstationary signals. Recent works have demonstrated that EMD has remarkable effect in time series decomposition, but EMD also has several problems such as scale mixture and convergence property. This paper proposes two key points to design Bandwid
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Du, Wei, and Quan Liu. "A Novel Empirical Mode Decomposition Denoising Scheme." Advanced Materials Research 143-144 (October 2010): 527–32. http://dx.doi.org/10.4028/www.scientific.net/amr.143-144.527.

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This paper presents a novel and fast scheme for signal denoising by using Empirical mode decomposition (EMD). The EMD involves the adaptive decomposition of signal into a series of oscillating components, Intrinsic mode functions(IMFs), by means of a decomposition process called sifting algorithm. The basic principle of the method is to reconstruct the signal with IMFs previously selected and thresholded. The denoising method is applied to four simulated signals with different noise levels and the results compared to Wavelets, EMD-Hard and EMD-Soft methods.
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FALTERMEIER, R., A. ZEILER, A. M. TOMÉ, A. BRAWANSKI, and E. W. LANG. "WEIGHTED SLIDING EMPIRICAL MODE DECOMPOSITION." Advances in Adaptive Data Analysis 03, no. 04 (2011): 509–26. http://dx.doi.org/10.1142/s1793536911000891.

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The analysis of nonlinear and nonstationary time series is still a challenge, as most classical time series analysis techniques are restricted to data that is, at least, stationary. Empirical mode decomposition (EMD) in combination with a Hilbert spectral transform, together called Hilbert-Huang transform (HHT), alleviates this problem in a purely data-driven manner. EMD adaptively and locally decomposes such time series into a sum of oscillatory modes, called Intrinsic mode functions (IMF) and a nonstationary component called residuum. In this contribution, we propose an EMD-based method, cal
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Dissertations / Theses on the topic "Emperical Mode Decomposition (EMD)"

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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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Tomás, Ana Raquel Dias. "Application of empirical mode decomposition (EMD) to chronological series of active fires from MODIS satellite." Master's thesis, ISA/UTL, 2011. http://hdl.handle.net/10400.5/4481.

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Mestrado em Engenharia Florestal e dos Recursos Naturais - Instituto Superior de Agronomia<br>Fire is a global phenomenon, acting as an important disturbance process. Africa is one of the continents that has higher fire density, particularly in savanna regions, making it the subject of innumerous studies about fire regime and behavior. Here, a new method of time series analysis called Empirical Mode Decomposition (EMD) was applied to monthly fire counts time series from MODIS Terra/Aqua sensors. The goals were to analyze the differences between the time series from the two instruments (MODIS T
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Abderahman, Huthaifa. "An Integrated Compensation System Based on Empirical Mode Decomposition for Robust Noninvasive Blood Pressure Estimation." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/35314.

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When it comes to monitoring human health, accuracy is not a choice. Accuracy in blood pressure (BP) estimation is essential for proper diagnosis and management of hypertension. An error of 5 mmHg is so serious, it can be responsible for doubling or halving number of patients diagnosed with hypertension. Motion artifacts are external sources of inaccuracy and can be due to sudden arm motion, muscle tremor, shivering, and transport vehicle vibration. Medium term drift, due to changing environmental factors, such as ambient temperature, can also contribute to the inaccuracy. Long term drift (agei
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Sadeghi, Mehdi. "Potential of the Empirical Mode Decomposition to analyze instantaneous flow fields in Direct Injection Spark Ignition engine : Effect of transient regimes." Thesis, Orléans, 2017. http://www.theses.fr/2017ORLE2069/document.

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Cette étude introduit une nouvelle approche appelée Bivariate 2D-EMD pour séparer le mouvement organisé à grande échelle, soit la composante basse fréquence de l’écoulement des fluctuations turbulentes, soit la composante haute fréquence dans un champ de vitesse instantané bidimensionnel.Cette séparation nécessite un seul champ de vitesse instantané contrairement aux autres méthodes plus couramment utilisées en mécanique des fluides, comme le POD. La méthode proposée durant cette thèse est tout à fait appropriée à l’analyse des écoulements qui sont intrinsèquement instationnaires et non linéai
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Waindim, Mbu. "On Unsteadiness in 2-D and 3-D Shock Wave/Turbulent Boundary Layer Interactions." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1511734224701396.

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Šlancar, Matěj. "Potlačení driftu signálu EKG s využitím empirického rozkladu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2017. http://www.nusl.cz/ntk/nusl-316450.

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The aim of this thesis is to introduce with principle of Empirical Mode Decomposition method and possibility use for correction of baseline wander in ECG signals. The thesis describes the main components of the ECG signal, a selection of possible types of signal noise, its property and principles of chosen methods for filtration of ECG signals. In conclusion the evaluation of the effectiveness of the EMD method for filtering a baseline wander and it comparing with effectiveness of the linear filtration. Functionality of used algorithms has been tested on signals of CSE standard library.
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De, Sanctis Silvia [Verfasser], and Hans Robert [Akademischer Betreuer] Kalbitzer. "Application of Singular Spectrum Analysis (SSA), Independent Component Analysis (ICA) and Empirical Mode Decomposition (EMD) for automated solvent suppression and automated baseline and phase correction from multi-dimensional NMR spectra / Silvia De Sanctis. Betreuer: Hans Robert Kalbitzer." Regensburg : Universitätsbibliothek Regensburg, 2011. http://d-nb.info/1030178941/34.

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Procházka, Petr. "Odstraňovaní kolísání izolinie v EKG pomocí empirické modální dekompozice." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-221366.

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In this semestral thesis, realizations of chosen linear filters for baseline wander are described. These filters are then used on artificial ECG signals from CSE database with added baseline wander. These methods are compared and results are evaluated. After that, literature search of Empirical mode decomposition method is utilized. Realization of designed filters in MATLAB programming language are described, then results are evaluated with respect to filtration success.
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Fayad, Farah. "Apprentissage et annulation des bruits impulsifs sur un canal CPL indoor en vue d'améliorer la QoS des flux audiovisuels." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2012. http://tel.archives-ouvertes.fr/tel-00769953.

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Le travail présenté dans cette thèse a pour objectif de proposer et d'évaluer les performances de différentes techniques de suppression de bruit impulsif de type asynchrone adaptées aux transmissions sur courants porteurs en lignes (CPL) indoor. En effet, outre les caractéristiques physiques spécifiques à ce type de canal de transmission, le bruit impulsif asynchrone reste la contrainte sévère qui pénalise les systèmes CPL en terme de QoS. Pour remédier aux dégradations dues aux bruits impulsifs asynchrones, les techniques dites de retransmission sont souvent très utilisées. Bien qu'elles soie
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Mettke, Philipp. "Vorhersagbarkeit ökonomischer Zeitreihen auf verschiedenen zeitlichen Skalen." Bachelor's thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-197876.

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This thesis examines three decomposition techniques and their usability for economic and financial time series. The stock index DAX30 and the exchange rate from British pound to US dollar are used as representative economic time series. Additionally, autoregressive and conditional heteroscedastic simulations are analysed as benchmark processes to the real data. Discrete wavelet transform (DWT) uses wavelike functions to adapt the behaviour of time series on different time scales. The second method is the singular spectral analysis (SSA), which is applied to extract influential reconstructed m
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Book chapters on the topic "Emperical Mode Decomposition (EMD)"

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Masuda, Makoto, and Taichi Shiiba. "Temporal and Frequency Analysis with Empirical Mode Decomposition for Vehicle Vibration Signals." In Lecture Notes in Mechanical Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70392-8_67.

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AbstractThis study presents the empirical mode decomposition method (EMD) for vehicle vibration and a correlation detection approach for input from road and vehicle body vibration using the Hilbert-Huang transform (HHT). Although the magnitude squared coherence is commonly used to examine the correlation of vehicle vibration with road input, it is not suitable for non-stationary vibration. On the other hand, the Hilbert-Huang transform (HHT) which consists of EMD and the Hilbert transform is proposed. This method is suitable for transient vibration analysis, while the drawbacks to intermittenc
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Labate, Domenico, Fabio La Foresta, Giuseppe Morabito, Isabella Palamara, and Francesco Carlo Morabito. "On the Use of Empirical Mode Decomposition (EMD) for Alzheimer’s Disease Diagnosis." In Advances in Neural Networks: Computational and Theoretical Issues. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18164-6_12.

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Wang, Heming, Richard Mann, and Edward R. Vrscay. "A Diffusion-Based Two-Dimensional Empirical Mode Decomposition (EMD) Algorithm for Image Analysis." In Lecture Notes in Computer Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93000-8_34.

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Chi, Pham Thi Kim, Vo Nhut Tuan, Nguyen Hoai Thuong, Ho Thi Kieu Khanh, Hui Yu, and Nguyen Duc Thang. "Noise Removal of Functional Near Infrared Spectroscopy Signals Using Emperical Mode Decomposition and Independent Component Analysis." In 6th International Conference on the Development of Biomedical Engineering in Vietnam (BME6). Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4361-1_156.

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Jatia, Nikita, and Karan Veer. "Performance Comparison of Denoising Methods for Fetal Phonocardiography Using Fir Filter and Empirical Mode Decomposition (EMD)." In Optimization Methods for Engineering Problems. Apple Academic Press, 2023. http://dx.doi.org/10.1201/9781003300731-12.

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Tabrizi, A., L. Garibaldi, A. Fasana, and S. Marchesiello. "Influence of Stopping Criterion for Sifting Process of Empirical Mode Decomposition (EMD) on Roller Bearing Fault Diagnosis." In Lecture Notes in Mechanical Engineering. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39348-8_33.

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Chang, H. C., P. L. Lee, and C. H. Wu. "Empirical Mode Decomposition (EMD) – Based Spatiotemporal Approach for Single-Trial Extraction of Post-Movement MEG Beta Synchronization." In IFMBE Proceedings. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03882-2_290.

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Fatmawati, T. Y., A. Yuliani, M. A. Afandi, and D. Zulherman. "Comparative Analysis of the Phonocardiogram Denoising System Based-on Empirical Mode Decomposition (EMD) and Double-Density Discrete Wavelet Transform (DDDWT)." In Proceedings of the 1st International Conference on Electronics, Biomedical Engineering, and Health Informatics. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6926-9_52.

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Panda, Saroj Kumar, Papia Ray, and Debani Prasad Mishra. "Short Term Load Forecasting Using Empirical Mode Decomposition (EMD), Particle Swarm Optimization (PSO) and Adaptive Network-Based Fuzzy Interference Systems (ANFIS)." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49339-4_17.

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Cooper, S. Morris, Liu Tianyou, and Innocent Ndoh Mbue. "Unveiling Potential Field Seperation with Emperical Mode Decomposition." In Research Advances in Environment, Geography and Earth Science Vol. 2. B P International, 2024. http://dx.doi.org/10.9734/bpi/raeges/v2/7966e.

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Conference papers on the topic "Emperical Mode Decomposition (EMD)"

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Das, Daisy, Nitin Choudhury, Nabamita Deb, Vaskar Deka, Manoj Kumar Deka, and Shikhar Kumar Sarma. "Enhanced Signal Decomposition Using Golay-Optimized Empirical Mode Decomposition (Go-EMD)." In 2024 International Conference on Recent Progresses in Science, Engineering and Technology (ICRPSET). IEEE, 2024. https://doi.org/10.1109/icrpset64863.2024.10955941.

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Zhao, Yong-tao, and Xing-peng Guo. "Time-Frequency Signal De-Noising of Coulostatically -Induced Transients Based on Empirical Mode Decomposition." In CORROSION 2007. NACE International, 2007. https://doi.org/10.5006/c2007-07458.

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Abstract A method of de-noising based on empirical mode decomposition (EMD) for coulostatically-induced transients (CITs) is presented. This filtering was illustrated with CIT and its associated impedance spectra, and comparisons have been made with wavelet de-noising and FIR method. The results reported here demonstrate that EMD de-noising is applicable to coulostatic measurements data in both the time and frequency domains, where wavelet filtering can also be successful. Moreover, in cases where the non-linear CITs need de-noise, EMD can eliminate noisy data from CIT. The proposed method sho
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Shi, Jiaxin, Jun Hu, Huapeng Zhao, Wei Chen, Min Zhang, and Zhiwei Gao. "Analyzing Transient Phenomena in the Time Domain Using Empirical Mode Decomposition(EMD)." In 2024 IEEE 12th Asia-Pacific Conference on Antennas and Propagation (APCAP). IEEE, 2024. https://doi.org/10.1109/apcap62011.2024.10881315.

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Tang, Fujian, Lizhi Zhao, Hong-Nan Li, et al. "Spatial Variation Analysis of Localized Corrosion of Steel Bar with Spectral Analysis Technique." In CONFERENCE 2022. AMPP, 2022. https://doi.org/10.5006/c2022-17792.

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Abstract This study aims to statistically analyze the distribution characteristics of localized corrosion along the length of corroded steel bars with spectral analysis techniques. Steel bars were embedded in a concrete prism and subjected to accelerated corrosion to levels ranging from 5.0 wt.% to 30.0 wt.% mass loss. After the corrosion test, the corroded steel bars were taken out of the concrete and cleaned with a sand blaster, and then scanned with a 3D laser scanner. The scanned point clouds were processed with an image processing software to determine the residual cross-sectional area di
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Tychkov, Alexander, Alan Alimuradov, and Pyotr Churakov. "The emperical mode decomposition for ECG signal preprocessing." In 2019 3rd School on Dynamics of Complex Networks and their Application in Intellectual Robotics (DCNAIR). IEEE, 2019. http://dx.doi.org/10.1109/dcnair.2019.8875613.

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Gladkova, Irina, Leonid Roytman, Mitchell D. Goldberg, and John Weber. "Compression of AIRS data using Emperical Mode Decomposition." In Optical Science and Technology, the SPIE 49th Annual Meeting, edited by Hung-Lung A. Huang and Hal J. Bloom. SPIE, 2004. http://dx.doi.org/10.1117/12.558967.

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Li, Ke, Jean-Yves Hogrel, Jacques Duchene, and David Hewson. "Analysis of Sustained Maximal Grip Contractions using emperical mode decomposition." In 2010 3rd International Conference on Biomedical Engineering and Informatics (BMEI). IEEE, 2010. http://dx.doi.org/10.1109/bmei.2010.5640090.

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Jai-Andaloussi, Said, Abderrahim Sekkaki, Gwenole Quellec, Mathieu Lamard, Guy Cazuguel, and Christian Roux. "Mass segmentation in mammograms by using Bidimensional Emperical Mode Decomposition BEMD." In 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2013. http://dx.doi.org/10.1109/embc.2013.6610780.

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Fan, Xianfeng, and Ming J. Zuo. "Gearbox Fault Detection Using Empirical Mode Decomposition." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-59349.

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Local faults in a gearbox cause impacts and the collected vibration signal is often non-stationary. Identification of impulses within the non-stationary vibration signal is key to fault detection. Recently, the technique of Empirical Mode Decomposition (EMD) was proposed as a new tool for analysis of non-stationary signal. EMD is a time series analysis method that extracts a custom set of bases that reflects the characteristic response of a system. The Intrinsic Mode Functions (IMFs) within the original data can be obtained through EMD. We expect that the change in the amplitude of the special
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Zhang, Hao, Jin He, Meng Zhu, and Zhanhua Huang. "Temporal phase retrieval in dynamic speckle interferometry by adaptive emperical mode decomposition." In Photonics Asia, edited by Kevin G. Harding, Peisen S. Huang, and Toru Yoshizawa. SPIE, 2012. http://dx.doi.org/10.1117/12.999617.

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