Academic literature on the topic 'Wavelet energy entropy'
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Journal articles on the topic "Wavelet energy entropy"
Li, Su Ping, and Yao Ling Fan. "Investigation of Sensor Fault Diagnosis in Air Handling Units Based on Wavelet Energy Entropy." Advanced Materials Research 645 (January 2013): 316–19. http://dx.doi.org/10.4028/www.scientific.net/amr.645.316.
Full textRaghu, S., N. Sriraam, and G. Pradeep Kumar. "Effect of Wavelet Packet Log Energy Entropy on Electroencephalogram (EEG) Signals." International Journal of Biomedical and Clinical Engineering 4, no. 1 (January 2015): 32–43. http://dx.doi.org/10.4018/ijbce.2015010103.
Full textZhang, Ai Hua, Ming Chun Kou, Chen Diao, and Dong Mei Lin. "Quality Assessment of ECG Signal Based on Wavelet Energy Ratio and Wavelet Energy Entropy." Applied Mechanics and Materials 530-531 (February 2014): 577–80. http://dx.doi.org/10.4028/www.scientific.net/amm.530-531.577.
Full textYan, Jian Guo, Dong Li Yuan, Si Yuan Li, and Xiao Jun Xing. "Study on Sensor Signal Filtering Based on Wavelet Energy Entropy." Applied Mechanics and Materials 63-64 (June 2011): 573–78. http://dx.doi.org/10.4028/www.scientific.net/amm.63-64.573.
Full textSun, Zeng Shou, Ke Ju Fan, Xu Guang Yin, and Peng Jie Han. "The Research of Civil Structural Damage Identification Based on Lifting Wavelet Entropy Index." Advanced Materials Research 291-294 (July 2011): 2041–48. http://dx.doi.org/10.4028/www.scientific.net/amr.291-294.2041.
Full textChen, Li, Jian Shen, Bin Zhou, Qingsong Wang, and Giuseppe Buja. "Quantitative Analysis on the Proportion of Renewable Energy Generation Based on Broadband Feature Extraction." Applied Sciences 12, no. 21 (November 3, 2022): 11159. http://dx.doi.org/10.3390/app122111159.
Full textKumar, Yatindra, Mohan Lal Dewal, and Radhey Shyam Anand. "Relative wavelet energy and wavelet entropy based epileptic brain signals classification." Biomedical Engineering Letters 2, no. 3 (September 2012): 147–57. http://dx.doi.org/10.1007/s13534-012-0066-7.
Full textBing, Hankun, Yuzhu Zhao, Le Pang, and Minmin Zhao. "Research on Fault Diagnosis Model of Rotating Machinery Vibration Based on Information Entropy and Improved SVM." E3S Web of Conferences 118 (2019): 02036. http://dx.doi.org/10.1051/e3sconf/201911802036.
Full textSun, Zhiqiang, Shuai Shao, and Hui Gong. "Gas–liquid Flow Pattern Recognition Based on Wavelet Packet Energy Entropy of Vortex-induced Pressure Fluctuation." Measurement Science Review 13, no. 2 (April 1, 2013): 83–88. http://dx.doi.org/10.2478/msr-2013-0016.
Full textGöksu, Hüseyin. "Engine Speed–Independent Acoustic Signature for Vehicles." Measurement and Control 51, no. 3-4 (April 2018): 94–103. http://dx.doi.org/10.1177/0020294018769080.
Full textDissertations / Theses on the topic "Wavelet energy entropy"
Santos, Mikaelle Oliveira. "An?lise Ac?stica de Desvios Vocais Infantis utilizando a Transformada Wavelet." reponame:Repositório Institucional do IFPB, 2016. http://repositorio.ifpb.edu.br/jspui/handle/177683/258.
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Dist?rbios da voz podem atingir diferentes faixas et?rias, afetando a qualidade vocal, prejudicando a comunica??o por meio da voz. T?cnicas de processamento digital de sinais de voz podem ser empregadas para auxiliar outros m?todos de avalia??o de dist?rbios da voz, tais como an?lise otorrinolaringol?gica e an?lise perceptivo-auditiva. Crian?as com dist?rbios de voz podem apresentar efeitos negativos no seu desenvolvimento social, educacional e f?sico. A investiga??o e o diagn?stico precoce do desvio vocal infantil permite maior efic?cia no tratamento. Entretanto, a avalia??o de desordens vocais em crian?as apresenta alguns desafios relacionados ?s dificuldades de coopera??o das mesmas durante os exames tradicionais. Nesta pesquisa, as medidas de energia e entropia dos coeficientes de detalhe da transformada wavelet s?o empregadas na avalia??o da qualidade vocal em crian?as. Dois estudos de caso s?o abordados nesta pesquisa: 1) An?lise ac?stica do grau da intensidade do desvio vocal; e 2) An?lise ac?stica da qualidade vocal predominante (rugosidade e soprosidade). As medidas de energia e entropia dos coeficientes de detalhe da transformada wavelet s?o utilizadas de maneira individual e combinada a fim de se obter uma maior efic?cia na classifica??o dos sinais. Para o primeiro estudo de caso, utilizando-se de um vetor h?brido de medidas combinadas, foram obtidas acur?cias acima de 95% e, para o segundo, utilizando-se tamb?m do vetor de medidas combinadas, as medidas de acur?cia foram superiores a 90%. Os sinais das vozes desviadas apresentaram eleva??o em suas frequ?ncias dos formantes, comparados ?s vozes sem desvio. Os resultados obtidos nesta pesquisa indicam que o uso das medidas de energia e entropia dos coeficientes de detalhe da transformada wavelet mostra-se como uma t?cnica promissora, que pode ser considerada para ser empregada como uma ferramenta para an?lise ac?stica da qualidade vocal em crian?as.
Li, Feng_Yu, and 李豐裕. "Wavelet Energy Entropy Applied to Detection Enhancement of Islanding Operation of Distributed Generation Systems." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/23956821646444188290.
Full text國立成功大學
電機工程學系碩博士班
96
The islanding operation of distributed generation systems happens when the distributed generators are disconnected from the mains power such that the load is purely supplied by those connected distributed generators. Under such scenarios, if the occurred event is not informed in time, it may damage the electric power equipment and affect the safety of operation personnel. In view of this importance, the thesis has devoted to the study of islanding operation detection via the wavelet energy entropy method. It is found that by employing the proposed method, it would help quantify the waveform such that energy distribution of voltage as well as frequency is better grasped, thus assisting the forewarning of the occurrence of islanding events. To confirm the feasibility of the method, the simulated model has been tested by the proposed approach and FPGA validation. Test results help support the method for the islanding detection enhancement of distributed generation systems.
Book chapters on the topic "Wavelet energy entropy"
Fernandez, Jincy J., and Nithyanandam Pandian. "Iris Recognition Using Integer Wavelet Transform and Log Energy Entropy." In Lecture Notes in Electrical Engineering, 15–29. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6987-0_2.
Full textYan, Yan. "Gingivitis Detection by Wavelet Energy Entropy and Linear Regression Classifier." In Intelligent Computing Theories and Application, 185–97. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-84532-2_17.
Full textLang, Kuan, Zongyi Xing, Wei Dong, and Xudong Gao. "A Rail Corrugation Detection Method Based on Wavelet Packet Energy Entropy." In Lecture Notes in Electrical Engineering, 205–14. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7989-4_21.
Full textMuszkats, Juan P., Miguel E. Zitto, Miryam Sassano, and Rosa Piotrkowski. "Application of Wavelet Transform to Damage Detection in Brittle Materials via Energy and Entropy Evaluation of Acoustic Emission Signals." In Applications of Wavelet Multiresolution Analysis, 75–88. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61713-4_5.
Full textDing, Kai, Xinghua Li, Hao Li, Huayuan Ma, Lei Fan, and Xiaogang Qi. "Wavelet Packet Energy Entropy Based Feature Analysis of Seismic Signals from Vehicle Targets." In Advances in Intelligent Systems and Computing, 153–58. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5887-0_22.
Full textNowak, W., E. Szul-Pietrzak, and A. Hachol. "Wavelet Energy and Wavelet Entropy as a New Analysis Approach in Spontaneous Fluctuations of Pupil Size Study – Preliminary Research." In IFMBE Proceedings, 807–10. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-00846-2_200.
Full textZhang, Yuanyuan, Qingwu Gong, and Xi Shi. "A Novel Adaptive Reclosure Criterion for HV Transmission Lines Based on Wavelet Packet Energy Entropy." In Advances in Neural Networks – ISNN 2009, 874–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01513-7_95.
Full textZhang, Bowen, Bingdie Huang, Qun Wu, Guowei Lu, and Yao Wu. "Research on the Analysis of Muscle Fatigue Based on the Algorithm of Wavelet Packet Entropy in sEMG." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2022. http://dx.doi.org/10.3233/faia220040.
Full textLiu, Xiao-Ming, Yang Zhao, Yun-Dong Cao, and Chun-Guang Hou. "Modeling research of low voltage AC arc fault based on the wavelet energy entropy." In Environment, Energy and Sustainable Development, 1187–91. CRC Press, 2013. http://dx.doi.org/10.1201/b16320-245.
Full textKumar, Himanshu, Nagarajan Ganapathy, Subha D. Puthankattil, and Ramakrishnan Swaminathan. "Classification of Emotional States Using EEG Signals and Wavelet Packet Transform Features." In Studies in Health Technology and Informatics. IOS Press, 2022. http://dx.doi.org/10.3233/shti220632.
Full textConference papers on the topic "Wavelet energy entropy"
Vora, Rita A., V. A. Bharadi, and H. B. Kekre. "Retinal scan recognition using wavelet energy entropy." In 2012 International Conference on Communication, Information & Computing Technology (ICCICT). IEEE, 2012. http://dx.doi.org/10.1109/iccict.2012.6398120.
Full textLi, Rui, Nan-hua Yu, Ming Gong, Yi-dan Su, Bin-bin Zhang, Bing-kun Xu, and Chun-xiang Li. "Fault diagnosis algorithm for distribution line based on wavelet singular entropy and wavelet energy entropy." In 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). IEEE, 2017. http://dx.doi.org/10.1109/iaeac.2017.8054451.
Full textYang, He, Xiubing Jing, Zehui Zheng, and Peng Shang. "Chatter Detection Based on Wavelet Packet Energy Entropy." In 2022 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO). IEEE, 2022. http://dx.doi.org/10.1109/3m-nano56083.2022.9941603.
Full textYan, Yan, and Dimas Lima. "Alcoholism via wavelet energy entropy and support vector machine." In UCC '21: 2021 IEEE/ACM 14th International Conference on Utility and Cloud Computing. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3492323.3495617.
Full textHui Liu, GuoHai Liu, and Yue Shen. "Lifting wavelet scheme and wavelet energy entropy theory for transient power quality detection." In 2008 7th World Congress on Intelligent Control and Automation. IEEE, 2008. http://dx.doi.org/10.1109/wcica.2008.4592853.
Full textShuai Wang, Tianshu Bi, and Ke Jia. "Wavelet entropy based fault detection approach for MMC-HVDC lines." In 2015 IEEE Power & Energy Society General Meeting. IEEE, 2015. http://dx.doi.org/10.1109/pesgm.2015.7286582.
Full textXuewei, Wang, Zhao Yong, and Wang Lin. "Best Wavelet Packet Power Measurement Based on Energy Threshold Entropy." In 2011 International Conference on Intelligent Computation Technology and Automation (ICICTA). IEEE, 2011. http://dx.doi.org/10.1109/icicta.2011.100.
Full textWang, Zhicheng, Yan Tian, Jian Liu, and Jinwen Tian. "Wavelet fusion method based on local energy and local entropy." In Visual Communications and Image Processing 2005. SPIE, 2005. http://dx.doi.org/10.1117/12.633205.
Full textLiu, Cuicui, Feng Wang, Fang Zhuo, and Ziqian Zhang. "Fault Diagnosis of HVDC Transmission System Using Wavelet Energy Entropy and the Wavelet Neural Network." In 2020 22nd European Conference on Power Electronics and Applications (EPE'20 ECCE Europe). IEEE, 2020. http://dx.doi.org/10.23919/epe20ecceeurope43536.2020.9215964.
Full textBesbes, Salsabil, and Zied Lachiri. "Wavelet packet energy and entropy features for classification of stressed speech." In 2016 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA). IEEE, 2016. http://dx.doi.org/10.1109/sta.2016.7952076.
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