Relevant bibliographies by topics / Chirplets

Contents

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

Academic literature on the topic 'Chirplets'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Chirplets"

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WU, XUEMING, and DEJIE YU. "ATOMIC DECOMPOSITION METHOD BASED ON ADAPTIVE CHIRPLET DICTIONARY." Advances in Adaptive Data Analysis 04, no. 01n02 (2012): 1250012. http://dx.doi.org/10.1142/s1793536912500124.

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We propose an atomic decomposition method (AD) based on adaptive chirplet dictionary for decomposing multicomponent nonstationary signals with polygonal instantaneous frequencies (IFs). These signals are waveforms of the very general form ∑ Ai(t) cos (φi(t)), where the phase φi(t) is time-varying and the amplitude Ai(t) is slowly varying. Different from the traditional four-parameters chirplet, the one applied in this paper only contains two parameters (chirp offset and chirp rate) and its IF can be regarded as a line on the time–frequency (TF) plane. The idea is to use matching pursuit (MP) a
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Xu, Chang, Cong Wang, and Jingbo Gao. "Instantaneous Frequency Identification Using Adaptive Linear Chirplet Transform and Matching Pursuit." Shock and Vibration 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/1762010.

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An instantaneous frequency identification method of vibration signal based on linear chirplet transform and Wigner-Ville distribution is presented. This method has an obvious advantage in identifying closely spaced and time-varying frequencies. The matching pursuit algorithm is employed to select optimal chirplets, and a modified version of chirplet transform is presented to estimate nonlinear varying frequencies. Because of the high time resolution, the modified chirplet transform is superior to the original method. The proposed method is applied to time-varying systems with both linear and n
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Boßmann, Florian, and Jianwei Ma. "Asymmetric chirplet transform — Part 2: Phase, frequency, and chirp rate." GEOPHYSICS 81, no. 6 (2016): V425—V439. http://dx.doi.org/10.1190/geo2015-0696.1.

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An asymmetric chirplet transform, also called the asymmetric Gaussian chirplet model (AGCM), was recently introduced for fast and accurate extraction of important information from seismic signals. Unlike Fourier or wavelet transforms with fixed base functions, the AGCM is an adaptive sparse representation based on the physical parameters of the given data. The atoms of AGCM, so-called chirplets, display asymmetric oscillation-attenuation properties. The AGCM decomposes seismic signals into nonstationary compressed plane waves. The waves or atoms consist of two parts with seven physical paramet
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Candès, E. J., P. R. Charlton, and H. Helgason. "Gravitational wave detection using multiscale chirplets." Classical and Quantum Gravity 25, no. 18 (2008): 184020. http://dx.doi.org/10.1088/0264-9381/25/18/184020.

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Valiere, J. C., F. Poisson, C. Depollier, and L. Simon. "High-speed moving source analysis using chirplets." IEEE Signal Processing Letters 6, no. 5 (1999): 113–15. http://dx.doi.org/10.1109/97.755431.

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Bultan, A. "A four-parameter atomic decomposition of chirplets." IEEE Transactions on Signal Processing 47, no. 3 (1999): 731–45. http://dx.doi.org/10.1109/78.747779.

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Mann, S., and S. Haykin. "‘Chirplets’ and ‘warblets’: novel time–frequency methods." Electronics Letters 28, no. 2 (1992): 114. http://dx.doi.org/10.1049/el:19920070.

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Kuttig, Helge, Marc Niethammer, Stefan Hurlebaus, and Laurence J. Jacobs. "Model-based analysis of dispersion curves using chirplets." Journal of the Acoustical Society of America 119, no. 4 (2006): 2122–30. http://dx.doi.org/10.1121/1.2177587.

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Mihovilović, D., and R. N. Bracewell. "Whistler analysis in the time-frequency plane using chirplets." Journal of Geophysical Research 97, A11 (1992): 17199. http://dx.doi.org/10.1029/92ja01140.

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Wang, X., J. Liu, H. Meng, and Y. Liu. "Novel atomic decomposition algorithm for parameter estimation of multiple superimposed Gaussian chirplets." IET Radar, Sonar & Navigation 5, no. 8 (2011): 854. http://dx.doi.org/10.1049/iet-rsn.2011.0012.

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Dissertations / Theses on the topic "Chirplets"

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Bardainne, Thomas. "Étude de la sismicité de Lacq et analyse des formes d'ondes par décomposition en chirplets." Phd thesis, Université de Pau et des Pays de l'Adour, 2005. http://tel.archives-ouvertes.fr/tel-00011997.

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Le gisement de gaz de Lacq est exploité depuis 1957 et la sismicité induite a débuté en 1969. De magnitude modérée (M <= 4.4), cette sismicité est induite par l'extraction des fluides. Après nettoyage de la base de données disponible (1989-1997), un Pointé Automatique dont les paramètres sont optimisés par Recuit Simulé a permis la mise à jour de la base de données. Ajoutés aux données pointées entre 1974 et 1988 et grâce à un modèle de vitesse 3D, plus 1600 évènements ont été localisés, la plupart dans et au dessus du réservoir. La confrontation des localisations des hypocentres et des mécani
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Bardainne, Thomas. "Etude de la sismicité de Lacq et analyse des formes d'ondes par décomposition en chirplets." Pau, 2005. https://tel.archives-ouvertes.fr/tel-00011997.

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De magnitude modérée, la sismicité est induite par l'extraction des fluides. Après nettoyage de la base de données disponible et un Pointé Automatique dont les paramètres sont optimisés par Recuit Simulé plus de 1600 évènements ont été localisés. La confrontation des localisations des hypocentres et des mécanismes aux foyers avec des informations apportées par les forages et la sismique 3D a permis de localiser les différents essaims de séismes au niveau de failles relativement importantes et orientées préférentiellement pour accommoder la perturbation de contrainte. La sismicité est localisée
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Kerber, Florian. "Dispersive Wave Analysis using the Chirplet Transform." Thesis, Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/14116.

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Time-frequency representations (TFR) are a widely used tool to analyze signals of guided waves such as Lamb waves. As a consequence of the uncertainty principle, however, the resolution in time and frequency is limited for all existing TFR methods. Due to the multi-modal and dispersive character of Lamb waves, displacement or energy related quantities can only be allocated to individual modes when they are separated in the time-frequency plane. The chirplet transform has been introduced as a generalization of both the wavelet and Short-time Fourier transform. It offers additional degrees of f
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Bettadapura, Raghuprasad Shivatejas. "Echo Delay Estimation to Aid Source Localization in Noisy Environments." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/50517.

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Time-delay estimation (TDE) finds application in a variety of problems, be it locating fractures or steering cameras towards the speaker in a multi-participant conference application. Underwater acoustic OFDM source localization is another important application of TDE. Existing underwater acoustic source localization techniques use a microphone array consisting of three or four sensors in order to effectively locate the source. Analog-to-digital (ADC) converters at these sensors call for a non-nominal investment in terms of circuitry and memory. A relatively inexpensive source localization
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Cui, Jie. "Adaptive chirplet transform for the analysis of visual evoked potentials." 2006. http://link.library.utoronto.ca/eir/EIRdetail.cfm?Resources__ID=449825&T=F.

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Books on the topic "Chirplets"

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Cui, Jie. Adaptive chirplet transform for the analysis of visual evoked potentials. 2006.

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Book chapters on the topic "Chirplets"

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Cui, Jie, and Willy Wong. "Visual Evoked Potential Analysis Using Adaptive Chirplet Transform." In Advanced Biosignal Processing. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-89506-0_11.

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Hui, Ali, and Hui Lin. "Chirplet-Fractal Characteristics of Leakage Current on HV Insulators." In Advances in Intelligent and Soft Computing. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25185-6_22.

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Hu, Guo-Sheng, Feng-Feng Zhu, and Yong-Jun Tu. "Power Quality Disturbance Detection and Classification Using Chirplet Transforms." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11903697_5.

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Shinde, Sonal Suhas, and Swati S. Kamthekar. "Person Authentication Using EEG Signal that Uses Chirplet and SVM." In Computational Vision and Bio-Inspired Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37218-7_39.

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Li, Yifei, and Zunhua Guo. "An Adaptive Chirplet Filter for Range Profiles Automatic Target Recognition." In Advances in Neural Networks – ISNN 2019. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22808-8_35.

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Dugnol, B., C. Fernández, G. Galiano, and J. Velasco. "On a Chirplet Transform Based Method for Co-channel Voice Separation." In Biomedical Engineering Systems and Technologies. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-92219-3_12.

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Bahoura, Mohammed, and Yvan Simard. "Chirplet Transform Applied to Simulated and Real Blue Whale (Balaenoptera musculus) Calls." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-69905-7_34.

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Yu, Haibin, Qianjin Guo, Jingtao Hu, and Aidong Xu. "Rolling Bearings Fault Diagnosis Based on Adaptive Gaussian Chirplet Spectrogram and Independent Component Analysis." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11881070_46.

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Mann, Steve. "Wavelets and "Chirplets": Time–Frequency "Perspectives" With Applications." In Advances in Machine Vision. WORLD SCIENTIFIC, 1992. http://dx.doi.org/10.1142/9789814355841_0006.

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"Accurate Detection of Weld Defects Using Chirplet Transform." In International Conference on Computer and Automation Engineering, 4th (ICCAE 2012). ASME Press, 2012. http://dx.doi.org/10.1115/1.859940.paper8.

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Conference papers on the topic "Chirplets"

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Moody, Daniela I., Steven P. Brumby, Kary L. Myers, and Norma H. Pawley. "Sparse classification of rf transients using chirplets and learned dictionaries." In 2011 45th Asilomar Conference on Signals, Systems and Computers. IEEE, 2011. http://dx.doi.org/10.1109/acssc.2011.6190351.

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Correas-Serrano, Aitor, and Maria A. Gonzalez-Huici. "Sparse Reconstruction of Chirplets for Automotive FMCW Radar Interference Mitigation." In 2019 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM). IEEE, 2019. http://dx.doi.org/10.1109/icmim.2019.8726758.

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Chassande-Mottin, Éric, Archana Pai, and Olivier Rabaste. "Chains of chirplets for the detection of gravitational wave chirps." In Optical Engineering + Applications, edited by Dimitri Van De Ville, Vivek K. Goyal, and Manos Papadakis. SPIE, 2007. http://dx.doi.org/10.1117/12.733966.

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Blackledge, J., and O. Iakovenko. "On the Application of Two-dimensional Chirplets for Resilient Digital Image Watermarking." In 24th IET Irish Signals and Systems Conference (ISSC 2013). Institution of Engineering and Technology, 2013. http://dx.doi.org/10.1049/ic.2013.0023.

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Pukhova, Valentina M., and Maria S. Stepanova. "Up-Chirplet and Down-Chirplet Transforms of Non-Stationary Signals." In 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). IEEE, 2019. http://dx.doi.org/10.1109/eiconrus.2019.8657179.

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Mann, S., and S. Haykin. "Time-frequency perspectives: the 'chirplet' transform." In [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE, 1992. http://dx.doi.org/10.1109/icassp.1992.226187.

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Mobasseri, Bijan G., and Amro Lulu. "LPI waveform design using chirplet graphs." In OCEANS 2015 - MTS/IEEE Washington. IEEE, 2015. http://dx.doi.org/10.23919/oceans.2015.7401968.

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Amiri, Reza, Mohammad Alaee, Hussein Rahmani, and Mohsen Firoozmand. "Chirplet Based Denoising of Reflected RADAR Signals." In 2009 Third Asia International Conference on Modelling & Simulation (AMS 2009). IEEE, 2009. http://dx.doi.org/10.1109/ams.2009.54.

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Weruaga, Luis. "Redundant time-frequency marginals for chirplet decomposition." In 2012 IEEE International Workshop on Machine Learning for Signal Processing (MLSP). IEEE, 2012. http://dx.doi.org/10.1109/mlsp.2012.6349775.

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Alaee, Mohammad, and Hamidreza Amindavar. "Chirplet-based target recognition using RADAR technology." In 2008 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM). IEEE, 2008. http://dx.doi.org/10.1109/sam.2008.4606910.

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