Electrónica y Computación
Ingeniería en Electrónica y Computación
 
   Misión y Visión
   Plan de Estudios
   Perfil de Ingreso
   Perfil de Egreso
   Campo Laboral
   Perspectivas
   Titulación
   Coordinador de Carrera
   Tutorías
   Planta Docente
   Video de la Carrera
   Galeria
   Contacto directo
 
   
 
 
CURRICULUM electronica
Nombre: Dr. Iván Esteban Villalón Turrubiates
Miembro del Sistema Nacional de Investigadores: Candidato
Correo electrónico: ivan.villaon@profesores.valles.udg.mx
Formación Acdémica:
Ingeniería en Mecánica.
Maestría en Ciencias en Ingeniería Eléctrica
Doctorado en Ciencias
Publicaciones:
Publicaciones en Conferencias Científicas Internacionales
  1. Ivan E. Villalon-Turrubiates, Roberto Rojas-Laguna y Santiago Serrano-Arellano, “Comparison Among
    Booth’s and Pekmestzi’s Algorithms for the Multiplication of Two Numbers”, en Proceedings of the
    International Conference on Devices, Circuits and Systems (CIDCSVER), Veracruz México, Junio 2003, versión
    electrónica.
  2. Ivan E. Villalon-Turrubiates, Oscar G. Ibarra-Manzano, Yuriy S. Shmaliy y Jose A. Andrade-Lucio, “Three-
    Dimensional Optimal Kalman Algorithm for GPS-Based Positioning Estimation of the Stationary Object”, en
    Proceedings of the IEEE International Conference on Advanced Optoelectronics and Lasers (CAOL), Alushta
    Ucrania, Septiembre 2003, pp. 274-277.
  3. Roberto Olivera-Reyna, Reynel Olivera-Reyna, Ivan E. Villalon-Turrubiates y Yuriy S. Shmaliy, “Simulation
    of the GPS-Based Steering of the Local Clock Time Errors Involving Optimal and Sub-Optimal FIR and Kalman
    Filters”, en Proceedings of the IEEE International Conference on Advanced Optoelectronics and Lasers
    (CAOL), Alushta Ucrania, Septiembre 2003, pp. 278-281.
  4. Ivan E. Villalon-Turrubiates, Jose A. Andrade-Lucio y Oscar G. Ibarra-Manzano, “Multidimensional Digital
    Signal Estimation Using Kalman’s Theory for Computer-Aided Applications”, en Proceedings of the
    International Conference on Computing, Communications and Control Technologies (CCCT), Austin E.U.A.,
    Agosto 2004, pp. 48-53.
  5. Yuriy V. Shkvarko e Ivan E. Villalon-Turrubiates, “Intelligent Processing of Remote Sensing Imagery for
    Decision Support in Environmental Resource Management: A Neural Computing Paradigm”, en Proceedings of
    the 16th Information Resources Management Association (IRMA) International Conference, San-Diego E.U.A.,
    Mayo 2005, pp. 1060-1062.
  6. Yuriy V. Shkvarko e Ivan E. Villalon-Turrubiates, “Real-Time Reconstruction of Remote Sensing Imagery:
    Aggregation of Robust Regularization with Neural Computing”, en Proceedings of the 17th International
    Association for Mathematics and Computers in Simulation (IMACS) World Congress, París Francia, Julio 2005,
    versión electrónica.
  7. Yuriy V. Shkvarko e Ivan E. Villalon-Turrubiates, “Simulation Study of the Unified Bayesian-Regularization
    Technique for Enhanced Radar Imaging”, en Proceedings of the 2nd International Radio Electronic Forum
    (IREF), Kharkov Ucrania, Septiembre 2005, versión electrónica.
  8. Ivan E. Villalon-Turrubiates, “Filtration and Enhancement of Environmental Characteristics Extracted from
    SAR Imagery Using Dynamic Kalman Technique”, en Proceedings of the 3rd International Workshop on
    Random Fields Modeling and Processing in Inhomogeneous Media (RFMPIM), Guanajuato México, Octubre
    2005, pp. 16-18.
  9. Yuriy V. Shkvarko e Ivan E. Villalon-Turrubiates, “Unified Bayesian-Experiment Design Regularization
    Technique for High-Resolution of the Remote Sensing Imagery”, en Proceedings of the 1st IEEE International
    Workshop on Computational Advances in Multi-Sensor adaptive processing (CAMSAP), Puerto-Vallarta
    México, Diciembre 2005, pp. 165-168.
  10. Yuriy V. Shkvarko, Jose L. Leyva-Montiel e Ivan E. Villalon-Turrubiates, “Neural Network Computational
    Technique for High-Resolution Remote Sensing Image Reconstruction with System Fusion”, en Proceedings of
    the 1st IEEE International Workshop on Computational Advances in Multi-Sensor adaptive processing
    (CAMSAP), Puerto-Vallarta México, Diciembre 2005, pp. 169-172.
  11. Ivan E. Villalon-Turrubiates y Yuriy V. Shkvarko, “Cognitive Reconstructive Remote Sensing for Decision
    Support in Environmental Resource Management”, en Proceedings of the 17th Information Resources
    Management Association (IRMA) International Conference, Washington D.C. E.U.A., Mayo 2006, pp. 978-980.
  12. Ivan E. Villalon-Turrubiates, “Intelligent Processing for SAR Imagery for Environmental Management”, en
    Proceedings of the 17th Information Resources Management Association (IRMA) International Conference,
    Washington D.C. E.U.A., Mayo 2006, pp. 981-983.
  13. Yuriy V. Shkvarko, Jose L. Leyva-Montiel e Ivan E. Villalon-Turrubiates, “Unifying the Experiment Design
    and Constrained Regularization Paradigms for Reconstructive Imaging with Remote Sensing Data”, en
    Proceedings of the IEEE International Conference on Image Processing (ICIP), Atlanta E.U.A., Octubre 2006,
    pp. 3241-3244.
  14. Yuriy V. Shkvarko e Ivan E. Villalon-Turrubiates, “Dynamical Enhancement of the Large Scale Remote
    Sensing Imagery for Decision Support in Environmental Resource Management”, en Proceedings of the 18th
    Information Resources Management Association (IRMA) International Conference, Vancouver Canada, Mayo
    2007, pp. 1335-1337.
  15. Ivan E. Villalon-Turrubiates, “Dynamical Analysis of Hydrological Indexes Extracted from Remote Sensing
    Imagery: An Introductory Study”, en Proceedings of the 4th IEEE International Workshop on the Analysis of
    Multi-Temporal Remote Sensing Imagery (MULTITEMP), Leuven Bélgica, Julio 2007, versión electrónica.
  16. Ivan E. Villalon-Turrubiates y Yuriy V. Shkvarko, “Dynamical Post-Processing of Environmental Electronic
    Maps Extracted from Large Scale Remote Sensing Imagery”, en Proceedings of the IEEE International
    Geoscience and Remote Sensing Symposium (IGARSS), Barcelona España, Julio 2007, versión electrónica.
  17. Yuriy V. Shkvarko, Ivan E. Villalon-Turrubiates y Jose L. Leyva-Montiel, “Remote Sensing Signature Fields
    Reconstruction via Robust Regularization of Bayesian Minimum Risk Technique”, en Proceedings of the 2nd
    IEEE International Workshop on Computational Advances in Multi-Sensor adaptive processing (CAMSAP), St.
    Thomas Islas Vírgenes E.U.A., Diciembre 2007, version electrónica.
Publicaciones en Revistas Científicas Internacionales:
  • Yuriy V. Shkvarko, Ivan E. Villalon-Turrubiates y Jose L. Leyva-Montiel, “Aggregation of Robust
    Regularization with Dynamic Filtration for Enhanced Radar Imaging”, Journal of Applied Radioelectronics
    (JAR), vol. 5, no. 3, pp. 316-325, Marzo 2006.
  • Yuriy Shkvarko e Ivan-Esteban Villalon-Turrubiates, “Computational Enhancement of Large Scale
    Environmental Imagery: Aggregation of Robust Numerical Regularization, Neural Computing and Digital
    Dynamic Filtering”, International Journal of Computational Science and Engineering (IJCSE), a ser publicado.
Publicaciones de Capítulos en Libros:
  • Yuriy Shkvarko, Rene Vazques-Bautista e Ivan Villalon-Turrubiates, “Fusion of Bayesian Maximum Entropy
    Spectral Estimation and Variational Analysis Methods for Enhanced Radar Imaging”, en Advanced Concepts for
    Intelligent Vision Systems, J. Blanc-Talon, W. Philips, D. Popescu and P. Scheunders, Ed. Holanda: Springer,
    2006, pp. 109-120.
  • Yuriy Shkvarko e Ivan Villalon-Turrubiates, “Remote Sensing Imagery and Signature Fields Reconstruction
    via Aggregation of Robust Regularization with Neural Computing”, en Advanced Concepts for Intelligent Vision
    Systems, J. Blanc-Talon, W. Philips, D. Popescu and P. Scheunders, Ed. Holanda: Springer, 2006, pp. 865-876.
electronicaelectronica
 
 
     

© 2008 Centro Universitario de los Valles
Carretera Guadalajara - Ameca Km. 45.5 C.P. 46600. Ameca, Jalisco, México.
Teléfonos 01 (375) 758 0148 y 758 0500
Comentarios y sugerencias sobre esta página: veganet@valles.udg.mx
Sitio web desarrollado con tecnología ASP.net 1.1
Valid XHTML 1.0 Transitional   Valid CSS