Relevant bibliographies by topics / Kullback-Leibler Distance

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

Academic literature on the topic 'Kullback-Leibler Distance'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Kullback-Leibler Distance"

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Kim, Sang-Hyun. "Video Content Indexing using Kullback-Leibler Distance." International Journal of Contents 5, no. 4 (2009): 51–54. http://dx.doi.org/10.5392/ijoc.2009.5.4.051.

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Rahmani, Somayeh, Vahid Khajehvand, and Mohsen Torabian. "Kullback-Leibler distance criterion consolidation in cloud." Journal of Network and Computer Applications 170 (November 2020): 102789. http://dx.doi.org/10.1016/j.jnca.2020.102789.

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Luan, Yu, Hong Zuo Li, and Ya Fei Wang. "Acoustic Features Selection of Speaker Verification Based on Average KL Distance." Applied Mechanics and Materials 373-375 (August 2013): 629–33. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.629.

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This paper proposes a new Average Kullback-Leibler distance to make an optimal feature selection algorithm for the matching score fusion of speaker verification. The advantage of this novel distance is to overcome the shortcoming of the asymmetry of conventional Kullback-Leibler distance, which can ensure the accuracy and robustness of the computation of the information content between matching scores of two acoustic features. From the experimental results by a variety of fusion schemes, it is found that the matching score fusion between MFCC and residual phase gains most information content.
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Nielsen, Frank. "On Voronoi Diagrams on the Information-Geometric Cauchy Manifolds." Entropy 22, no. 7 (2020): 713. http://dx.doi.org/10.3390/e22070713.

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We study the Voronoi diagrams of a finite set of Cauchy distributions and their dual complexes from the viewpoint of information geometry by considering the Fisher-Rao distance, the Kullback-Leibler divergence, the chi square divergence, and a flat divergence derived from Tsallis entropy related to the conformal flattening of the Fisher-Rao geometry. We prove that the Voronoi diagrams of the Fisher-Rao distance, the chi square divergence, and the Kullback-Leibler divergences all coincide with a hyperbolic Voronoi diagram on the corresponding Cauchy location-scale parameters, and that the dual
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Qian, Dongyun, and Huifeng Jin. "Distance Metric with Kullback–Leibler Divergence for Classification." International Journal of Signal Processing, Image Processing and Pattern Recognition 10, no. 7 (2017): 157–66. http://dx.doi.org/10.14257/ijsip.2017.10.7.14.

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Kulhavý, Rudolf. "A Kullback-Leibler distance approach to system identification." Annual Reviews in Control 20 (January 1996): 119–30. http://dx.doi.org/10.1016/s1367-5788(97)00010-2.

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Coetzee, Frans M. "Correcting the Kullback–Leibler distance for feature selection." Pattern Recognition Letters 26, no. 11 (2005): 1675–83. http://dx.doi.org/10.1016/j.patrec.2005.01.014.

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Kulhavý, R. "A Kullback-Leibler distance approach to system identification." Annual Review in Automatic Programming 20 (1996): 119–30. http://dx.doi.org/10.1016/s0066-4138(97)00010-4.

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Jabari, Shabnam, Mohammad Rezaee, Fatemeh Fathollahi, and Yun Zhang. "Multispectral change detection using multivariate Kullback-Leibler distance." ISPRS Journal of Photogrammetry and Remote Sensing 147 (January 2019): 163–77. http://dx.doi.org/10.1016/j.isprsjprs.2018.11.014.

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Veldhuis, R. "The centroid of the symmetrical Kullback-Leibler distance." IEEE Signal Processing Letters 9, no. 3 (2002): 96–99. http://dx.doi.org/10.1109/97.995827.

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Dissertations / Theses on the topic "Kullback-Leibler Distance"

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Soman, Salil 1975. "Rigid registration of Echoplanar and conventional magnetic resonance images by minimizing the Kullback-Leibler distance." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/87859.

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Foster, Eric D. "State space time series clustering using discrepancies based on the Kullback-Leibler information and the Mahalanobis distance." Diss., University of Iowa, 2012. https://ir.uiowa.edu/etd/3455.

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In this thesis, we consider the clustering of time series data; specifically, time series that can be modeled in the state space framework. Of primary focus is the pairwise discrepancy between two state space time series. The state space model can be formulated in terms of two equations: the state equation, based on a latent process, and the observation equation. Because the unobserved state process is often of interest, we develop discrepancy measures based on the estimated version of the state process. We compare these measures to discrepancies based on the observed data. In all, seven novel
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Cabella, Brenno Caetano Troca. "Inferência estatística em métodos de análise de ressonância magnética funcional." Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/59/59135/tde-10062008-072315/.

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No presente trabalho, conceitos de inferência estatística são utilizados para aplicação e comparação de diferentes métodos de análise de sinais de ressonância magnética funcional. A idéia central baseia-se na obtenção da distribuição de probabilidade da variável aleatória de interesse, para cada método estudado e sob diferentes valores da relação sinal-ruído (SNR). Este objetivo é atingido através de simulações numéricas da função resposta hemodinâmica (HRF) acrescida de ruído gaussiano. Tal procedimento nos permite avaliar a sensibilidade e a especificidade dos métodos empregados através da c
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Gunay, Melih. "Representation Of Covariance Matrices In Track Fusion Problems." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12609026/index.pdf.

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Covariance Matrix in target tracking algorithms has a critical role at multi- sensor track fusion systems. This matrix reveals the uncertainty of state es- timates that are obtained from diferent sensors. So, many subproblems of track fusion usually utilize this matrix to get more accurate results. That is why this matrix should be interchanged between the nodes of the multi-sensor tracking system. This thesis mainly deals with analysis of approximations of the covariance matrix that can best represent this matrix in order to efectively transmit this matrix to the demanding site. Kullback-Leib
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Martín, Fernández Josep Antoni. "Medidas de diferencia y clasificación automática no paramétrica de datos composicionales." Doctoral thesis, Universitat Politècnica de Catalunya, 2001. http://hdl.handle.net/10803/6704.

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Es muy frecuente encontrar datos de tipo composicional en disciplinas tan dispares como son, entre otras, las ciencias de la tierra, la medicina, y la economía. También es frecuente en estos ámbitos el uso de técnicas de clasificación no paramétrica para la detección de agrupaciones naturales en los datos. Sin embargo, una búsqueda bibliográfica bastante exhaustiva y la presentación de resultados preliminares sobre el tema en congresos de ámbito internacional han permitido constatar la inexistencia de un cuerpo teórico y metodológico apropiado que permita desarrollar pautas y recomendaciones a
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Tsai, Ming-Jer, and 蔡明哲. "Spectral Unmixing Based on The Constrained Kullback-Leibler Distance." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/39079668129723714671.

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碩士<br>國立成功大學<br>資訊工程學系碩博士班<br>95<br>Due to limited spatial resolution, a pixel often consists of two or more substances in remote sensing imagery. Spectral unmixing techniques have been intensively used for determining the abundance of a substance, also referred to as an endmember, in a pixel. Most unmixing methods that derive endmembers directly from an image assume that there exist pure pixels in the image corresponding to the endmembers of interest. That is, the endmembers are the vertices of a simplest geometric shape that can enclose a space of a given dimension. However, this assumption
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Yoon, Sung Won. "A measure of soil structure derived from water retention properties a Kullback-Leibler distance approach /." 2009. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052177.

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Bröcker, Jochen. "Approximations and Applications of Nonlinear Filters." Doctoral thesis, 2003. http://hdl.handle.net/11858/00-1735-0000-0006-B55F-8.

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Books on the topic "Kullback-Leibler Distance"

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Tibshirani, Robert. A note on profile likelihood, least favourable families and Kullback-Leibler distance. University of Toronto, Dept. of Statistics, 1985.

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Book chapters on the topic "Kullback-Leibler Distance"

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Bigi, Brigitte. "Using Kullback-Leibler Distance for Text Categorization." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36618-0_22.

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Gan, Rui, Jue Wu, Albert C. S. Chung, Simon C. H. Yu, and William M. Wells. "Multiresolution Image Registration Based on Kullback-Leibler Distance." In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30135-6_73.

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Ingrassia, Salvatore. "Logistic Discrimination by Kullback-Leibler type Distance Measures." In Studies in Classification, Data Analysis, and Knowledge Organization. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-60126-2_12.

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Chung, Albert C. S., William M. Wells, Alexander Norbash, and W. Eric L. Grimson. "Multi-modal Image Registration by Minimising Kullback-Leibler Distance." In Medical Image Computing and Computer-Assisted Intervention — MICCAI 2002. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45787-9_66.

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Hu, Lei, Yan Ji, Yang Li, and Feng Gao. "SAR Image Segmentation Based on Kullback-Leibler Distance of Edgeworth." In Advances in Multimedia Information Processing - PCM 2010. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15702-8_50.

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Pinto, David, José-Miguel Benedí, and Paolo Rosso. "Clustering Narrow-Domain Short Texts by Using the Kullback-Leibler Distance." In Computational Linguistics and Intelligent Text Processing. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-70939-8_54.

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Cunha, Vanice Canuto, Arturo A. Z. Zavala, Pedro R. M. Inácio, Damien Magoni, and Mario M. Freire. "Classification of Encrypted Internet Traffic Using Kullback-Leibler Divergence and Euclidean Distance." In Advanced Information Networking and Applications. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44041-1_77.

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Pados, D., P. Papantoni-Kazakos, D. Kazakos, and A. Koyiantis. "The Use of the Kullback-Leibler Distance for Learning in Neural Binary Classifiers." In Proceedings of the First US/Japan Conference on the Frontiers of Statistical Modeling: An Informational Approach. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0854-6_13.

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Braess, Dietrich, Jürgen Forster, Tomas Sauer, and Hans U. Simon. "How to Achieve Minimax Expected Kullback-Leibler Distance from an Unknown Finite Distribution." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36169-3_30.

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Chung, Yong-Joo. "Using Kullback-Leibler Distance in Determining the Classes for the Heart Sound Signal Classification." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-88906-9_7.

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Conference papers on the topic "Kullback-Leibler Distance"

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John, Lee, Pierre Lambert, Edouard Couplet, et al. "Can MDS rival with t-SNE by using the symmetric Kullback-Leibler divergence\\ across neighborhoods as a pseudo-distance?" In ESANN 2025. Ciaco - i6doc.com, 2025. https://doi.org/10.14428/esann/2025.es2025-174.

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Washino, Tomohiro, and Tadashi Takahashi. "Kullback-Leibler Distance and Statatistical Model." In the International Conference on Modern research in Engineering, Technology & Science. Acavent, 2019. http://dx.doi.org/10.33422/icmets.2019.03.203.

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Wilson, J. N. "Landmine discrimination using the Kullback-Leibler distance." In Defense and Security Symposium, edited by Russell S. Harmon, J. Thomas Broach, and John H. Holloway, Jr. SPIE, 2007. http://dx.doi.org/10.1117/12.722284.

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Beheshti, Soosan. "Kullback-Leibler distance in linear parametric modeling." In 2008 IEEE International Symposium on Information Theory - ISIT. IEEE, 2008. http://dx.doi.org/10.1109/isit.2008.4595272.

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Sanchez, Claudia N., Sebastian Gutierrez, Julieta Dominguez Soberanes, and Mario Graff. "Landscape images distance using kullback leibler divergence." In 2018 International Conference on Research in Intelligent and Computing in Engineering (RICE). IEEE, 2018. http://dx.doi.org/10.1109/rice.2018.8627908.

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Vergara, Alexander, Mehmet K. Muezzinoglu, Nikolai Rulkov, and Ramon Huerta. "Kullback-Leibler distance optimization for artificial chemo-sensors." In 2009 IEEE Sensors. IEEE, 2009. http://dx.doi.org/10.1109/icsens.2009.5398579.

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Crysandt, Holger. "Linear feature vector compression using Kullback-Leibler distance." In 2006 IEEE International Symposium on Signal Processing and Information Technology. IEEE, 2006. http://dx.doi.org/10.1109/isspit.2006.270863.

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Boltz, Sylvain, Eric Debreuve, and Michel Barlaud. "kNN-based high-dimensional Kullback-Leibler distance for tracking." In Eighth International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS '07). IEEE, 2007. http://dx.doi.org/10.1109/wiamis.2007.53.

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Bouyeddou, Benamar, Benamar Kadri, Fouzi Harrou, and Ying Sun. "Nonparametric Kullback-Leibler distance-based method for networks intrusion detection." In 2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI). IEEE, 2020. http://dx.doi.org/10.1109/icdabi51230.2020.9325642.

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Ambika, A., J. Jennifer Ranjani, K. B. Srisathya, and P. Deepika. "Content based image retrieval using ripplet transform and Kullback-Leibler Distance." In 2014 International Conference on Computer Communication and Informatics (ICCCI). IEEE, 2014. http://dx.doi.org/10.1109/iccci.2014.6921759.

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Journal articles
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