Mostrar el registro sencillo del ítem

Knowledge discovery in databases from a perspective of intelligent information visualization

dc.rights.licensehttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.contributor.authorAlvarado-Pérez J.C.
dc.contributor.authorBolaños-Ramírez H.
dc.contributor.authorPeluffo-Ordóñez D.H.
dc.contributor.authorMurillo S.
dc.contributor.editorGuarin P.V.
dc.contributor.editorPosada L.G.
dc.contributor.other20th Symposium on Signal Processing, Images and Computer Vision, STSIVA 2015
dc.date.accessioned2024-12-02T20:15:32Z
dc.date.available2024-12-02T20:15:32Z
dc.date.issued2015
dc.identifier.isbn978-146739461-1
dc.identifier.urihttps://hdl.handle.net/20.500.14112/28909
dc.description.abstractThis paper reviews some recent and classical, relevant works on information visualization with a special focus on those applied to big data. The central idea dealt in this work relies on how to perform data mining tasks in a visual fashion, that is, using graphical correlation and interaction techniques. The scope of this review encompasses visualization techniques, formal visualization systems, and smart information visualization models. As well, newest approaches consisting of visualization and data mining integration process are explained. © 2015 IEEE.
dc.format.mediumRecurso electrónico
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.rights.uriAttribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
dc.source2015 20th Symposium on Signal Processing, Images and Computer Vision, STSIVA 2015 - Conference Proceedings
dc.sourceSymp. Signal Process., Images Comput. Vis., STSIVA - Conf. Proc.
dc.sourceScopus
dc.titleKnowledge discovery in databases from a perspective of intelligent information visualization
datacite.contributorFaculty of Engineering, Universidad de Salamanca, Universidad Mariana, Colombia
datacite.contributorFaculty of Engineering, Universidad Cooperativa de Colombia, Sede Pasto, Colombia
datacite.contributorGrupo de Investigación en Ingeniería de Software, Universidad Autónoma de Manizales, Colombia
datacite.contributorAlvarado-Pérez J.C., Faculty of Engineering, Universidad de Salamanca, Universidad Mariana, Colombia
datacite.contributorBolaños-Ramírez H., Faculty of Engineering, Universidad Cooperativa de Colombia, Sede Pasto, Colombia
datacite.contributorPeluffo-Ordóñez D.H., Faculty of Engineering, Universidad Cooperativa de Colombia, Sede Pasto, Colombia
datacite.contributorMurillo S., Grupo de Investigación en Ingeniería de Software, Universidad Autónoma de Manizales, Colombia
datacite.contributor20th Symposium on Signal Processing, Images and Computer Vision, STSIVA 2015
datacite.rightshttp://purl.org/coar/access_right/c_abf2
oaire.resourcetypehttp://purl.org/coar/resource_type/c_c94f
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aa
dc.contributor.sponsorPontificia Universidad Javeriana
dc.identifier.doi10.1109/STSIVA.2015.7330438
dc.identifier.instnameUniversidad Mariana
dc.identifier.local7330438
dc.identifier.reponameRepositorio Clara de Asis
dc.identifier.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84962915345&doi=10.1109%2fSTSIVA.2015.7330438&partnerID=40&md5=eb10cee8b7e1ed6621b65d5a7ec14629
dc.relation.conferencedate2 September 2015 through 4 September 2015
dc.relation.conferenceplaceBogota
dc.relation.iscitedby1
dc.relation.referencesHaykin S., Adaptive Filter Theory, Pearson Education, (2013)
dc.relation.referencesChassaig R., Digital Signal Processing and Applications with the C6713 and C6416 DSK, (2008)
dc.relation.referencesKehtarnavaz N., Kim N., Panahi I., Digital signal processing system design: Using LabVIEW and TMS320C6000, 11th IEEE Digital Signal Processing Workshop, and the 3rd IEEE Signal Processing Education Workshop, pp. 10-14, (2004)
dc.relation.referencesGan W.S., Teaching and learning the hows and whys of real-time digital signal processing, IEEE Trans. on Education, New York, 45, 4, pp. 336-343, (2002)
dc.relation.referencesBerisha S.V., Kwon H., Huang C., Natarajan A., Ferzili R., Using the Java-DSP Real-Time hardware interface in undergraduate classes, 36th ASEE/IEEE Annual Frontiers in Education Conference, pp. 12-17, (2006)
dc.relation.referencesGalanis M., Papazacharias A., Zigouris E., A DSP Course for Real-Time systems design and implementation based on the TMS320C6211 DSK, IEEE International Conf. on Digital Signal Processing, 2, pp. 853-856, (2002)
dc.relation.referencesGulfo L., Valencia J., Identificación y Modelamiento de Sistemas de Audio API Mediante Filtros Adaptativos, (2012)
dc.relation.referencesMillan D., Estudio y Comparativa de Diferentes Algoritmos Adaptativos Para la Identificación de Sistemas, (2012)
dc.relation.referencesDiniz P.S., Adaptive Filtering: Algorithms and Practical Implementation, (2008)
dc.relation.referencesQuanzhen H., Zhiyuan G., Shouwei G., Yong S., Xiaojin Z., Comparison of LMS and RLS algorithm for active vibration control of smart structures, Presented at Third International Conference on Measuring Technology and Mechatronics Automation ICMTMA?11, 1, 1, pp. 745-748, (2011)
dc.relation.referencesAgraval S., Gopal V., Performance analysis of adaptive filtering algorithms for system identification, International Journal of Electronics and Communication Engineering, 5, 2, pp. 207-217, (2012)
dc.relation.referencesSoria E., Calpe J., Chambers J., Martinez M., Camps G., Guerrero J.D., A novel approach to introducing adaptive filters based on the LMS algorithm and its variants, IEEE Trans. on Education, 47, pp. 127-133, (2008)
dc.relation.referencesReyes L.N., Análisis de Filtros Adaptativos de la Familia SM Aplicados Para El Diseño de un Cancelador de Eco Ac?stico, (2013)
dc.relation.referencesZhao H., Hu S., Li L., Wan X., NLMS adaptive FIR filter design method, IEEE Region 10 Conference TENCON, pp. 1-5, (2013)
dc.relation.referencesPaleologu C., Benesty J., Grant S.L., Osterwise C., Variable step-size NLMS algorithms for echo cancellation, Presented at Conf. Record of the Forty-third Asilomar Conference on Signals, Systems and Computers, pp. 633-637, (2009)
dc.relation.referencesFarhang B.B., Adaptive Filters Theory, Applications, (1999)
dc.relation.referencesCiochina S., Paleologu C., Benesty J., Enescu A., On the influence of the forgetting factor of the RLS adaptive filter in system identification, Signals, International Symposium on Circuits and Systems, ISSCS, 1, 1, pp. 1-4, (2009)
dc.relation.referencesGan W.S., Chong Y., Gong W., Tan W., Rapid prototyping for teaching real-time digital signal processing, IEEE Trans. on Education, New York, 43, 1, pp. 19-24, (2000)
dc.relation.referencesGannot S., Avrin V., A simulink® and Texas instruments C6713® based digital signal processing laboratory, 14th European Signal Processing Conference, EUSIPCO 2006, pp. 4-8, (2006)
dc.relation.referencesInstruments T., TMS320C6713, TMS320C6713B. Floating-Point Digital Signal Processors, (2005)
dc.relation.referencesDigital S., TMS320C6713 DSK, Technical Reference, (2003)
dc.relation.referencesInstruments T., TLV320AIC23B stereo audio CODEC, 8 to 96KHz, with integrated headphone amplifier, user manual, Texas Instruments Incorporated, (2004)
dc.relation.referencesAlvarez J., Chuez M., Vargas P., Implementaciones en matlab de los algoritmos adaptativos para los sistemas de antenas inteligentes, Revista Tecnológica ESPOL, 1, 1, (2011)
dc.relation.referencesKaoru D., Vitoria R., Arlindo V.L., Abrao T., Implementação eficiente de filtros adaptativos utilizando a plataforma TMS320C6713, Semina: Ciências Exatas e Tecnológicas, Londrina, 32, 1, pp. 115-131, (2011)
dc.relation.referencesHasnain S.K., Digital Signal Processing, (2009)
dc.relation.referencesSimulink, Simulation & Model Based Design, (2012)
dc.relation.referencesInstruments T., Code Composer Studio IDE Getting Started User's Guide v3.3, (2006)
dc.relation.referencesCompute Filtered Output, Filter Error, and Filter Weights for Given Input and Desired Signal Using RLS Adaptive Filter Algorithm-Simulink, (2014)
dc.relation.referencesPathak P.K., Sarma K.K., Time varying system identification using adaptive filter, IRNet Trans. on Electrical and Electronics Engineering, ITEEE?12, 1, 2, (2012)
dc.relation.referencesKara T., Eker I., Experimental nonlinear identification of a two mass system, IEEE Conference on Control Applications, CCA 2003, 1, pp. 66-71, (2003)
dc.relation.referencesDobra P., Duma R., Petreus D., Trusca M., Adaptive system identification and control using dsp for automotive power generation, Presented at 16th Mediterranean Conference on Control and Automation Congress Centre, (2008)
dc.relation.referencesLi Z., Li C., LMS and RLS algorithms comparative study in system identification, International Conference on Multimedia Technology, ICMT 2011, 1, 1, pp. 5428-5430, (2011)
dc.relation.referencesShafiq M., Ejaz S., Ahmed N., Hardware implementation of adaptive noise cancellation over DSP Kit TMS320C6713, International Journal of Signal Processing (SPIJ), 7, 1, (2013)
dc.relation.referencesDuran C.A., Reyes J.A., Sanchez J.C., Implementation and analysis of the NLMS algorithm on TMS320C6713 DSP, 52nd IEEE International Midwest Symposium on Circuits and Systems, MWSCAS '09, pp. 1091-1096, (2009)
dc.relation.referencesDjigan V.I., Adaptive filtering algorithms with quatratized cost function for Linearly Constrained arrays, IX International Conference on Antenna Theory and Techniques, ICATT?13, 1, pp. 214-216, (2013)
dc.relation.referencesSoumya R.G., Naveen N., Lal M.J., Application of adaptive filter using adaptive line enhancer techniques, Third International Conference on Advances in Computing and Communications, ICACC?13, 1, 1, pp. 165-168, (2013)
dc.relation.referencesXia Y., Jianchang L., Hongru L., Performance analysis of adaptive filters for time-varying systems, 32nd Chinese Control Conference, CCC?13, pp. 8572-8575, (2013)
dc.relation.referencesHuang Y.I., Wang Y.W., Meng F.J., Wang G.L., A spatial spectrum estimation algorithm based on adaptive beamforming nulling, Presented at Fourth International Conference on Intelligent Control and Information Processing, ICICIP'13, pp. 220-224, (2013)
dc.relation.referencesVijay J.P., Sharma N.K., Performance analysis of RLS over LMS algorithm for MSE in adaptive filters, International Journal of Technology Enhancements and Emerging Engineering Research, 2, 4, pp. 40-44, (2014)
dc.relation.referencesHameed A.A., Real-Time Noise Cancellation Using Adaptive Algorithms, (2012)
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.subject.keywordsComputer vision
dc.subject.keywordsData mining
dc.subject.keywordsData visualization
dc.subject.keywordsImage processing
dc.subject.keywordsInformation analysis
dc.subject.keywordsInformation science
dc.subject.keywordsInformation systems
dc.subject.keywordsSignal processing
dc.subject.keywordsVisualization
dc.subject.keywordsGraphical correlation
dc.subject.keywordsInformation visualization
dc.subject.keywordsIntegration process
dc.subject.keywordsIntelligent information
dc.subject.keywordsInteraction techniques
dc.subject.keywordsKnowledge discovery in database
dc.subject.keywordsVisualization system
dc.subject.keywordsVisualization technique
dc.subject.keywordsBig data
dc.type.driverinfo:eu-repo/semantics/conferenceObject
dc.type.hasversioninfo:eu-repo/semantics/acceptedVersion
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTDATA
dc.type.spaContribución a congreso / Conferencia


Ficheros en el ítem

FicherosTamañoFormatoVer

No hay ficheros asociados a este ítem.

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem