Relevant bibliographies by topics / Wavelet entropy

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Wavelet entropy'

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

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Journal articles on the topic "Wavelet entropy"

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Lweesy, K., N. Khasawneh, M. Fraiwan, H. Wenz, H. Dickhaus, and L. Fraiwan. "Classification of Sleep Stages Using Multi-wavelet Time Frequency Entropy and LDA." Methods of Information in Medicine 49, no. 03 (2010): 230–37. http://dx.doi.org/10.3414/me09-01-0054.

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Summary Background: The process of automatic sleep stage scoring consists of two major parts: feature extraction and classification. Features are normally extracted from the polysomno-graphic recordings, mainly electroencephalograph (EEG) signals. The EEG is considered a non-stationary signal which increases the complexity of the detection of different waves in it. Objectives: This work presents a new technique for automatic sleep stage scoring based on employing continuous wavelet transform (CWT) and linear discriminant analysis (LDA) using different mother wavelets to detect different waves
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Ahmadi, H., G. Dumont, F. Sassani, and R. Tafreshi. "Performance of Informative Wavelets for Classification and Diagnosis of Machine Faults." International Journal of Wavelets, Multiresolution and Information Processing 01, no. 03 (2003): 275–89. http://dx.doi.org/10.1142/s0219691303000189.

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This paper deals with an application of wavelets for feature extraction and classification of machine faults in a real-world machine data analysis environment. We have utilized informative wavelet algorithm to generate wavelets and subsequent coefficients that are used as feature variables for classification and diagnosis of machine faults. Informative wavelets are classes of functions generated from a given analyzing wavelet in a wavelet packet decomposition structure in which for the selection of best wavelets, concepts from information theory, i.e. mutual information and entropy are utilize
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Raghu, 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 (2015): 32–43. http://dx.doi.org/10.4018/ijbce.2015010103.

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The scaling behavior of human electroencephalogram (EEG) signals is well exploited by appropriate extraction of time – frequency domain and entropy based features. Such measurable inherently helps understanding the neurophysiological phenomenon of brain as well as its associated cortical activities. Being a non-linear time series, EEG's are assumed to be fragment of fluctuations. Several attempts have been made to study the EEG signals for clinical applications such as epileptic seizure detection, evoked response potential recognition, tumor detection, identification of alcoholics and so on. I
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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.

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This paper presents a novel fault diagnosis method for sensors in air-handling units based on wavelet energy entropy. Instead of directly comparing the numerous data under noise conditions, the wavelet energy entropy deviation is used for the fault detection and diagnosis. The actual Three-level wavelet analysis is used to decompose the measurement data captured from sensors first and then the concept of Shannon entropy is referred to define the wavelet energy entropy. Once the wavelet energy entropy is obtained, whether the sensors are faulty can be confirmed through comparing the deviation o
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Sun, 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.

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The failure of civil engineering structure will lead to heavy losses. So, identifying structural damage is necessary as early as possible. The excellent localization performance of lifting wavelet transform will facilitate significantly damage diagnosis. On the base of wavelet energy distribution of structural acceleration response, taking advantage of characteristics of lifting wavelet and entropy, the structural damage identification method based on lifting wavelet entropy is proposed in this paper. And the lifting wavelet time entropy index and the relative lifting wavelet entropy index are
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Pacheco, Julio César Ramírez, Joel Antonio Trejo-Sánchez, and Luis Rizo-Domínguez. "The shifted wavelet $ (q, q') $-entropy and the classification of stationary fractal signals." Networks and Heterogeneous Media 20, no. 1 (2025): 89–103. https://doi.org/10.3934/nhm.2025006.

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<p>In this article, a wavelet entropy, which behaves as a shifted version of the standard wavelet $ (q, q') $-entropy of fractal signals, is presented. The shifted wavelet $ (q, q') $-entropy is obtained by computing the standard $ (q, q') $-entropy functional on a weighted relative-wavelet-energy (RWE) representation of fractal signals; it is shown that the weight within the RWE plays the role of a shifting factor in the characteristics of the standard wavelet $ (q, q') $-entropy. Therefore the shifted wavelet $ (q, q') $-entropy relocates the wavelet entropy values to any point of the
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Jallouli, Malika, Sabrine Arfaoui, Anouar Ben Mabrouk, and Carlo Cattani. "Clifford Wavelet Entropy for Fetal ECG Extraction." Entropy 23, no. 7 (2021): 844. http://dx.doi.org/10.3390/e23070844.

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Analysis of the fetal heart rate during pregnancy is essential for monitoring the proper development of the fetus. Current fetal heart monitoring techniques lack the accuracy in fetal heart rate monitoring and features acquisition, resulting in diagnostic medical issues. The challenge lies in the extraction of the fetal ECG from the mother ECG during pregnancy. This approach has the advantage of being a reliable and non-invasive technique. In the present paper, a wavelet/multiwavelet method is proposed to perfectly extract the fetal ECG parameters from the abdominal mother ECG. In a first step
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Noori Hoshyar, Azadeh, Bijan Samali, Ranjith Liyanapathirana, and Saber Taghavipour. "Analysis of failure in concrete and reinforced-concrete beams for the smart aggregate–based monitoring system." Structural Health Monitoring 19, no. 2 (2019): 463–80. http://dx.doi.org/10.1177/1475921719854151.

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Monitoring of structures and defining the severity of damages that occur under loading are essential in practical applications of civil infrastructure. In this article, we analyze failure using a smart aggregate sensor–based approach. The signals captured by smart aggregate sensors mounted on the structure under loading are de-noised using wavelet de-noising technique to prevent misdirection of the event interpretation of what is happening in the material. The performance of different mother wavelets on the de-noising process was investigated and analyzed. The objective is to identify the opti
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Yang, Yan Mei, Ze Gen Wang, Yu Yun Gao, and Fa Peng Gao. "Deformation Monitoring Data De-Noising Processing Based on Wavelet Packet." Applied Mechanics and Materials 166-169 (May 2012): 1180–86. http://dx.doi.org/10.4028/www.scientific.net/amm.166-169.1180.

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Wavelet packet coefficients carrying real signals have large amplitude but are in minority, while those carrying noise has lower amplitude but is of large number. In this case, the Basic principle of de-noising wavelet packet is to process signals carrying noise. A suitable threshold is chosen in different decomposition level. Wavelet packet coefficient of less than this threshold is set to equal zero, while wavelet packet coefficients of greater than this threshold is reserved and reconstructed into de-noising signals. MSE, SNR, PSNR are regarded as the standards of de-noising evaluation, som
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Zhang, Mingming, Pan Kong, Anping Hou, Aiguo Xia, Wei Tuo, and Yongzhao Lv. "Identification Strategy Design with the Solution of Wavelet Singular Spectral Entropy Algorithm for the Aerodynamic System Instability." Aerospace 9, no. 6 (2022): 320. http://dx.doi.org/10.3390/aerospace9060320.

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In order to effectively identify the signs of instability in the aerodynamic system of an axial compressor, a wavelet singular spectral entropy algorithm incorporated within the wavelet transform, singular value decomposition and information entropy is proposed to describe the distribution complexity of the spatial modalities in the flow field. This kind of identification design can accurately distinguish the boundary between the stable and unstable states of the internal flow field from the view of a dynamic system. On the basis of the information entropy algorithm, the wavelet singular spect
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Dissertations / Theses on the topic "Wavelet entropy"

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Yi, Ju Y. "Definition and Construction of Entropy Satisfying Multiresolution Analysis (MRA)." DigitalCommons@USU, 2016. https://digitalcommons.usu.edu/etd/5057.

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This paper considers some numerical schemes for the approximate solution of conservation laws and various wavelet methods are reviewed. This is followed by the construction of wavelet spaces based on a polynomial framework for the approximate solution of conservation laws. Construction of a representation of the approximate solution in terms of an entropy satisfying Multiresolution Analysis (MRA) is defined. Finally, a proof of convergence of the approximate solution of conservation laws using the characterization provided by the basis functions in the MRA will be given.
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SILVA, MARCUS VINICIUS FONSECA DE ARAUJO. "IMAGE COMPRESSION USING WAVELET TRANSFORM AND TRELLIS CODE VECTOR QUANTIZATION WITH ENTROPY CONSTRAINT." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1998. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8684@1.

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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>MINISTÉRIO DA EDUCAÇÃO<br>Essa dissertação apresenta um codificador de imagens para baixas taxas de bits utilizando a decomposição da imagem em 10 sub-bandas através da aplicação da transformada wavelet. Uma técnica de redução de irrelevância visual é usada para descartar blocos de coeficientes das sub-bandas de alta freqüência (2 a 10). Os blocos remanescentes são classificados em bordas e não bordas e codificados através da técnica ECTCVQ ( Entropy-Constrained Trellis Coded Vector Quantization). Já a primeira sub-banda é
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SILVA, Israel Batista Freitas da. "Representações cache eficientes para índices baseados em Wavelet trees." Universidade Federal de Pernambuco, 2016. https://repositorio.ufpe.br/handle/123456789/21050.

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Submitted by Rafael Santana (rafael.silvasantana@ufpe.br) on 2017-08-30T19:22:34Z No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) Israel Batista Freitas da Silva.pdf: 1433243 bytes, checksum: 5b1ac5501cae385e4811343e1426e6c9 (MD5)<br>Made available in DSpace on 2017-08-30T19:22:34Z (GMT). No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) Israel Batista Freitas da Silva.pdf: 1433243 bytes, checksum: 5b1ac5501cae385e4811343e1426e6c9 (MD5) Previous issue date: 2016-12-12<br>CNPQ, FACEPE.<br>Hoje em d
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Budihal, Prasad Adhokshaja Achar. "Region of Interest Based Compression of Grayscale Images." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5842.

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Image compression based on Region of Interest (ROI) has been one of the hot topics of interest in image processing. There is not a single widely accepted method for detecting the ROI automatically form an image. To reduce the transmission bandwidth and storage space requirements of gray scale images, an algorithm is suggested for detecting the ROI automatically based on Tsallis entropy method. Tsallis entropy method is used to segment the image into two segments, the ROI and the background. These two segments can then be compressed at different rates, to avoid losing information in the ROI whi
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Goulart, Antonio José Homsi. "Classificação automática de gênero musical baseada em entropia e fractais." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/18/18153/tde-16032012-152801/.

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A classificação automática de gênero musical tem como finalidade o conforto de ouvintes de músicas auxiliando no gerenciamento das coleções de músicas digitais. Existem sistemas que se baseiam em cabeçalhos de metadados (tais como nome de artista, gênero cadastrado, etc.) e também os que extraem parâmetros dos arquivos de música para a realização da tarefa. Enquanto a maioria dos trabalhos do segundo tipo utilizam-se do conteúdo rítmico e tímbrico, este utiliza-se apenas de conceitos da teoria da informação e da geometria de fractais. Entropia, lacunaridade e dimensão do fractal são os parâmet
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Vitor, Avyner Lorran de Oliveira. "Detecção de falhas de estator em motores de indução trifásicos utilizando transformada wavelet, medida RMS e potência de previsão." Universidade Tecnológica Federal do Paraná, 2015. http://repositorio.utfpr.edu.br/jspui/handle/1/3194.

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O Motor de Indução Trifásico é a máquina elétrica mais utilizada no ambiente industrial. Trata-se de um equipamento que apresenta construção robusta, facilidade de manutenção, baixo custo de aquisição e confiabilidade. Contudo, em ambiente fabril, o mesmo está exposto a esforços térmicos, elétricos e mecânicos indesejáveis, os quais, com o passar do tempo, resultam em uma falha. A presente pesquisa consiste em analisar a falha de curto-circuito de estator, uma das falhas mais recorrentes em motores de indução. Para tanto, são investigadas as peculiaridades refletidas nos sinais de corrente est
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Yang, Jin. "A Dynamic and Thermodynamic Approach to Complexity." Thesis, University of North Texas, 2003. https://digital.library.unt.edu/ark:/67531/metadc4276/.

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The problem of establishing the correct approach to complexity is a very hot and crucial issue to which this dissertation gives some contributions. This dissertation considers two main possibilities, one, advocated by Tsallis and co-workers, setting the foundation of complexity on a generalized, non-extensive , form of thermodynamics, and another, proposed by the UNT Center for Nonlinear Science, on complexity as a new condition that, for physical systems, would be equivalent to a state of matter intermediate between dynamics and thermodynamics. In the first part of this dissertation, the conc
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Silva, Lyvia Regina Biagi. "Classificação de falhas em maquinas eletricas usando redes neurais, modelos wavelet e medidas de informação." Universidade Tecnológica Federal do Paraná, 2014. http://repositorio.utfpr.edu.br/jspui/handle/1/1201.

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CAPES; CNPq<br>Este trabalho apresenta uma proposta de metodologia para detecção e classificação de falhas em motores de indução trifásicos ligados diretamente à rede elétrica. O método proposto é baseado na análise dos sinais de corrente do estator, com e sem a presença de falhas nos rolamentos, estator e rotor. Um dos efeitos desses tipos de falhas é o aparecimento de componentes de frequência específicas, relacionados à velocidade de rotação da máquina. Os sinais foram analisados usando a decomposição wavelet-packet, que permite a avaliação dos sinais em bandas de frequência de tamanhos var
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St-Amant, Gabrielle. "Understanding the Hemodynamic Response and Sensory Contributions to Automatic Postural Control." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39554.

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The postural control-cognition dual-task literature has demonstrated greater postural stability through the examination of multiple kinetic and kinematic measures. Recently, sample entropy (SampEn) and wavelet discrete transform have supported the claim of automaticity, as higher SampEn values and a shift toward higher contribution from automatic sensory systems have been demonstrated in dual-task settings. In order to understand the cortical component of postural control, functional near-infrared spectroscopy (fNIRS) has been used to identify cortical activation under postural control conditi
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Li, Jing. "Digital Signal Characterization for Seizure Detection Using Frequency Domain Analysis." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-296861.

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Nowadays, a significant proportion of the population in the world is affected by cerebral diseases like epilepsy. In this study, frequency domain features of electroencephalography (EEG) signals were studied and analyzed, with a view being able to detect epileptic seizures more easily. The power spectrum and spectrogram were determined by using fast fourier transform (FFT) and the scalogram was found by performing continuous wavelet transform (CWT) on the testing EEG signal. In addition, two schemes, i.e. method 1 and method 2, were implemented for detecting epileptic seizures and the applicab
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Books on the topic "Wavelet entropy"

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Daniel, Sarit. Wavelet based artificial neural network and entropy detection techniques for a chaosmaker. National Library of Canada, 2002.

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Book chapters on the topic "Wavelet entropy"

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Yu, Francis T. S. "Wavelet Transforms with Optics." In Entropy and Information Optics. CRC Press, 2017. http://dx.doi.org/10.1201/b22443-10.

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Leeudomwong, T., and P. Woraratsoontorn. "Wavelet Entropy Detection of Heart Sounds." In Lecture Notes in Electrical Engineering. Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-84814-3_74.

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Bunluechokchai, S., and P. Tosaranon. "Analysis of Heart Sounds with Wavelet Entropy." In Lecture Notes in Electrical Engineering. Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-84814-3_72.

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Sassano, Myriam P., and Araceli N. Proto. "Housing Prices Wavelet Entropy to Understand Macroeconomic States." In Advanced Dynamic Modeling of Economic and Social Systems. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-32903-6_1.

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Wang, Wei. "Covid-19 Detection by Wavelet Entropy and Jaya." In Intelligent Computing Theories and Application. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-84532-2_45.

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Vampa, Victoria, María T. Martín, Lucila Calderón, and Aurelio F. Bariviera. "Wavelet Entropy and Complexity Analysis of Cryptocurrencies Dynamics." In Digital Era and Fuzzy Applications in Management and Economy. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94485-8_2.

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Kirichenko, Lyudmyla, Oksana Pichugina, Larysa Chala, and Tamara Radivilova. "Exploring Stochastic Time Series Structure Through Wavelet Entropy." In Lecture Notes on Data Engineering and Communications Technologies. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-70959-3_14.

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Li, Cui, and ZhiHai Lu. "Gingivitis Classification via Wavelet Entropy and Support Vector Machine." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51103-6_25.

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Han, Yang, Zhanhong Ma, Ping Zhou, and Zhicheng Liu. "Analysis of Parkinson gait based on wavelet packet entropy." In IFMBE Proceedings. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03889-1_121.

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Lu, Zhang. "Heart Sound Feature Extraction Based on Wavelet Singular Entropy." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-40861-8_60.

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Conference papers on the topic "Wavelet entropy"

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Prasanna, Ch Lakshmi, S. Ramana Kumar Joga, Sandhya Perla, Kushal Amarapini, Durga Prasad Prasadula, and Naveen Koyya. "Wavelet Entropy Measurement Based Power Quality Disturbances Diagnosis." In 2024 IEEE International Conference on Smart Power Control and Renewable Energy (ICSPCRE). IEEE, 2024. http://dx.doi.org/10.1109/icspcre62303.2024.10675175.

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Tianwen, Wu. "Dual Attention Entropy Model for Efficient Neural Image Compression." In 2024 21st International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP). IEEE, 2024. https://doi.org/10.1109/iccwamtip64812.2024.10873692.

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Ghorbanian, Parham, and Hashem Ashrafiuon. "A Numerical Study of Information Entropy in EEG Wavelet Analysis." In ASME 2016 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/dscc2016-9836.

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The purpose of this study is to numerically evaluate the performance of information entropy in electroencephalography (EEG) signal analysis. In particular, we use EEG data from an Alzheimer’s disease (AD) pilot study and apply several wavelet functions to determine the signals’ time and frequency characteristics. The wavelet entropy and wavelet sample entropy of the continuous wavelet transformed data are then determined at various scale ranges corresponding to major brain frequency bands. Non-parametric statistical analysis is then used to compare the entropy features of the EEG data obtained
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Li, Rui, Nan-hua Yu, Ming Gong, et al. "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.

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Brouzas, Spyridon, and Ioannis T. Georgiou. "Spatial Localization of Air Inclusions in Carbon Fiber T-Beam, by Use of Wavelet Entropy Time Series From Hammer Tap Test." In ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-67591.

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Abstract In this paper, a vibration-based method, called wavelet entropy time series, for non-destructive testing of carbon fiber specimens is introduced and demonstrated experimentally. The wavelet transform of vibration signals, acquired after an impact excitation of the specimen, is combined with Shannon’s informational entropy to quantify a trend in the disorder of the signal. Notions such as wavelet entropy, wavelet entropy time series are defined and utilized to assist in structural health monitoring. The scientific merit of the method was investigated both experimentally and computation
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Benzy VK, Jasmin EA, and Rachel Cheriyan Koshy. "Approximate Entropy and Wavelet Entropy based Depth of Anesthesia monitoring." In 2015 International Conference on Control Communication & Computing India (ICCC). IEEE, 2015. http://dx.doi.org/10.1109/iccc.2015.7432923.

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Pantin, Eric, and Jean-Luc Starck. "Wavelet transform and maximum entropy method." In SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, edited by Randall L. Barbour, Mark J. Carvlin, and Michael A. Fiddy. SPIE, 1995. http://dx.doi.org/10.1117/12.224171.

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Rizal, Achmad, Risanuri Hidayat, and Hanung Adi Nugroho. "Multilevel wavelet packet entropy: A new strategy for lung sound feature extraction based on wavelet entropy." In 2017 International Conference on Robotics, Automation and Sciences (ICORAS). IEEE, 2017. http://dx.doi.org/10.1109/icoras.2017.8308048.

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Brault, Patrice. "Bayesian Wavelet Domain Segmentation." In BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: 24th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering. AIP, 2004. http://dx.doi.org/10.1063/1.1835193.

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Mohammad-Djafari, Ali. "Wavelet Domain Image Separation." In BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: 22nd International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering. AIP, 2003. http://dx.doi.org/10.1063/1.1570545.

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Reports on the topic "Wavelet entropy"

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Danylchuk, H., V. Derbentsev, Володимир Миколайович Соловйов, and A. Sharapov. Entropy analysis of dynamic properties of regional stock markets. Society for Cultural and Scientific Progress in Central and Eastern Europe, 2016. http://dx.doi.org/10.31812/0564/1154.

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This paper examines entropy analysis of regional stock markets. We propose and empirically demonstrate the effectiveness of using such entropy as sample entropy, wavelet and Tsallis entropy as a measure of uncertainty and instability of such complex systems as regional stock markets. Our results show that these entropy measures can be effectively used as crisis prediction indicators.
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Шарапов, О. Д., та В. М. Соловйов. Використання вейвлет-ентропії для аналізу складних економічних систем. КНЕУ, 2008. http://dx.doi.org/10.31812/0564/1322.

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У роботі розглянуто методи розрахунку значень вейвлет-ентропії на основі дискретного та неперервного вейвлет-перетворення. За допомогою описаних методів проведено аналіз трьох економічних криз минулого сторіччя та зроблено висновки щодо можливості використання вейвлет-ентропії для дослідження економічних систем з точки зору наявності в їх функціонуванні критичних та кризових явищ. This paper Is devoted to the methods of calculation of values wavelet entropy based on discrete and continuous wavelet-transformation. By the described methods the analysis of three economic crises of past century is
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Johnson, Joseph E., and Vladimir Gudkov. Cyberspace Assurance Metrics: Utilizing Models of Networks, Complex Systems Theory, Multidimensional Wavelet Analysis, and Generalized Entrophy Measures. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada434351.

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You might also be interested in the extended bibliographies on the topic 'Wavelet entropy' for particular source types:
Journal articles Dissertations / Theses
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