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Publications

Peer-Reviewed Journal Papers Indexed in the Journal Citation Report
  1. Caporal, M. A. M., Magdaleno, J. D. J. R., Vega, I. C., & Caporal, R. M. (2017). An improved grid-photovoltaic system based on variable-step MPPT, predictive control, and active/reactive control. IEEE Latin America Transactions, 15(11), 2064-2070.

  2. Israel Cruz-Vega, Jose Rangel-Magdaleno, Roberto Morales Caporal, Juan Manuel Ramirez-Cortez, Omar Sandre. Parameter Identification of a PMSM using a Granular Computing Surrogate Model. Enviado a Transactions on Instrumentation and Measurements, IEEE.

  3. Jose Rangel-Magdaleno, Hayde Peregrina-Barreto, Juan Ramirez-Cortes, Israel Cruz-Vega, Hilbert Spectrum Analysis of Induction Motors for the Detection of Incipient Broken Rotor Bars, Measurement, Available online 1 June 2017, ISSN 0263-2241, https://doi.org/10.1016/j.measurement.2017.05.070. (http://www.sciencedirect.com/science/article/pii/S0263224117303792)

  4. Israel Cruz; Carlos A Reyes Garcia; Hugo J Escalante; Jose J Rangel; Juan M Ramirez,  Surrogate modeling based on granular models and fuzzy aptitude functions, Applied Soft Computing – Elsevier, https://doi.org/10.1016/j.asoc.2017.12.016

  5. Israel Cruz-Vega, Jose Rangel-Magdaleno, Juan Manuel Ramírez Cortés and Hayde Peregrina-Barreto, Automatic progressive damage detection of rotor bar in induction motor using vibration analysis and multiple classifiers, aceptado en “Journal of Mechanical Science and Technology”.

  6. Rangel-Magdaleno, J., Peregrina-Barreto, H., Ramirez-Cortes, J., Morales-Caporal, R., & Cruz-Vega, I. (2016). Vibration analysis of partially damaged rotor bar in induction motor under different load condition using DWT. Shock and Vibration, 2016.

  7. Cruz-Vega, I., & Escalante, H. J. (2016). An online and incremental GRLVQ algorithm for prototype generation based on granular computing. Soft Computing, 1-14.

  8. Israel Cruz-Vega, Hugo Jair Escalante, A note on “Adaptive fuzzy fitness granulation for evolutionary optimization”, International Journal of Approximate Reasoning, Volume 57, February 2015, Pages 40-43, ISSN 0888-613X, http://dx.doi.org/10.1016/j.ijar.2014.11.006

  9. Cruz-Vega Israel, Escalante Hugo J., Carlos A. Reyes,Jesus A. Gonzalez, Alejandro Rosales-Pérez. Surrogate modeling based on an Adaptive Network and Granular Computing, available online: February 7, 2015 SOFT COMPUTING, Springer.

  10. Cruz-Vega Israel, Wen Yu, Multiple fuzzy neural networks modeling with sparse data, Neurocomputing Journal, Elsevier, ISSN: 0925-2312. Vol. 73, No.13-15, 2446-2453, 2010

 

Peer-Reviewed International Conference Papers

 

  1. Israel Cruz-Vega, Omar Sandre-Hernandez, Jose de Jesus Rangel, Juan Manuel Ramirez, Roberto Morales, Surrogate Modeling and Knowledge Extraction in GA applied to a Parameter's Estimation Case. IEEE-Symposium Series on Computational Intelligence (IEEE-SSCI 2017), Honolulu, Hawaii.

  2. Cesar Hernandez-Gonzalez, Juan Manuel Ramirez-Cortes, José Rangel-Magdaleno, Israel Cruz-Vega, Pilar Gomez-Gil and Hayde Peregrina-Barreto. EEG motor imagery signals classification using maximum overlap wavelet transform and support vector machines, IEEE Autumn Meeting on Power, Electronics and Computing (ROPEC 2017)

  3. Sinahi Dionisio-Ortega, L. Oyuki Rojas-Perez, Jose Martinez-Carranza and Israel Cruz-Vega, "A Deep Learning Approach Towards Autonomous Flight in Forest Environments", aceptado en International Conference on Electronics, Communications and Computers (CONIELECOMP 2018)

  4. Roberto Morales-Caporal, Mario E. Leal-López, J. de Jesús Rangel-Magdaleno, Omar Sandre-Hernández, Israel Cruz-Vega, Direct Torque Control of a PMSM-Drive for Electric Vehicle Applications, aceptado en International Conference on Electronics, Communications and Computers (CONIELECOMP 2018).

  5. Israel Cruz-Vega, Hayde Peregrina-Barreto, Jose de Jesus Rangel-Magdaleno, Juan Manuel Ramirez-Cortes, and Leopoldo Altamirano-Robles. Automatic stellar spectral classification with multiple intelligent classifiers, 2017 IEEE Internacional Instrumentations and Measurement Technology Conference.

  6. Carlos Morales-Pérez, José de Jesús Rangel Magdaleno, Hayde Peregrina-Barreto, Juan Manuel Ramírez, Israel Cruz-Vega. FPGA-Based Broken Bar Detection on IM Using OMP Algorithm, IEEE International Instrumentation and Measurement Conference 2017

  7. Israel Cruz, Carlos Alberto Reyes, Juan Manuel Ramirez, Pilar Gomez and Jose de Jesus Rangel,  Genetic Algorithms based on a Granular Surrogate Model and Fuzzy Aptitude Functions, IEEE WCCI 2016.

  8. P. Gomez-Gil, J. Rangel-Magdaleno, J. M. Ramirez-Cortes, E. Garcia-Treviño and I. Cruz-Vega, "Intelligent identification of induction motor conditions at several mechanical loads," 2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings, Taipei, 2016, pp. 1-5.
    doi: 10.1109/I2MTC.2016.7520396

  9. Carlos Morales-Pérez, Jose Rangel-Magdaleno, Israel Cruz-Vega, Juan Ramirez-Cortes, Hayde Peregrina-Barreto, FPGA Implementation of Orthogonal Matching Pursuit Algorithm, 2016 13th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE),  Mexico, City. Mexico

  10. M. Morales-Caporal, Jose Rangel-Magdaleno, I. Cruz-Vega, R. Morales-Caporal, “Digital simulation of a predictive current control for photovoltaic system based on the mppt strategy”, 13th International Conference on Power Electronics, Guanajuato, Mexico, 20-23 Junio, 2016.

  11. Israel Cruz-Vega, Hugo Jair Escalante, Improved Learning Rule for LVQ based on Granular Computing, 7th Mexican Conference on Pattern Recognition (MCPR2015), artículo aceptado y por publicarse en Lecture Notes in Computer Science, Springer.

  12. Israel Cruz-Vega Garcia-Limon, Mauricio Hugo Jair Escalante Balderas,  ADAPTIVE-SURROGATE BASED ON A NEURO-FUZZY NETWORK AND GRANULAR COMPUTING, ISBN: 978-1-4503-2662-9,  Proceedings of the 2014 conference on Genetic and evolutionary computation, Vol. , Pag.761-768.

  13. Cruz Vega Israel and Wen Yu, Nonlinear System Modeling with a New Fuzzy Model and Neural Compensation, Advances in Neural Network Research and Applications, Springer-Verlgag, Lecture Notes in Electrical Engineering, LNEE 67, 117-127, 2010

  14. Cruz Vega Israel and Wen Yu, Multiple fuzzy neural networks modeling on sparse data based on a nonparametric regression technique, 11th IEEE International Conference on Information Reuse and Integration (IRI 2010), Las Vegas, USA, 304-307, 2010

  15. Cruz Vega Israel, Wen Yu, Juan Jose Cordova, Multiple Fuzzy Neural Networks Modeling with Sparse Data, 2010 IEEE International Conference on Fuzzy Systems, Fuzzy'10, Bacelona, Spain, 2010

  16. L. Moreno Ahedo, R. Carmona, R. Francisco, F. Ortiz, I. Cruz. On the implementation of a parametric oscillator in analog applications, Proceedings of the 8th International Caribbean Conference on Devices, Circuits and Systems (ICCDCS), 2012, In Press

  17. Cruz Vega Israel, Wen Yu, Luis Moreno, Adaptive indirect control with neuro fuzzy systems via kernel smoothing. MICAI 2012, San Luis Potosí, México, Artículo Publicado en revista Lecture Notes In Artifitial Intelligence de Springer, ISSN: 0302-9743

  18. Cruz-Vega, I.; Moreno-Ahedo, L.O., "Structure identification and adaptive control of neuro-fuzzy systems by a non-parametric regression technique," Electronics, Communications and Computing (CONIELECOMP), 2013 International Conference on , vol., no., pp.185,191, 11-13 March 2013 doi: 10.1109/CONIELECOMP.2013.6525783. 

 

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