Dr. Alma Y. Alanis

Research Professor
University of Guadalajara, Mexico

Highest Degree
Ph.D. in Electrical Engineering from University of Guadalajara, Mexico

My URL
https://livedna.org/52.18561

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Area of Interest:

Physical Science Engineering
Electrical Engineering
Neural Networks
Nonlinear Control
Data Analysis

Selected Publications

  1. Alanis, A.Y. and E.N. Sanchez, 2017. Discrete-Time Neural Observers. Academic Press, USA.

  2. Lopez-Franco, M., E.N. Sanchez, A.Y. Alanis and C. LOpez-Franco, 2016. Neural control for driving a mobile robot integrating stereo vision feedback. Neural Proces. Lett., 43: 425-444.
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  3. Alanis, A.Y., 2016. Real-time implementation of a discrete reduced order neural observer: Linear induction motors application. Intelli. Autom. Soft Comput., 22: 491-498.
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  4. Lopez-Franco, M., E.N. Sanchez, A.Y. Alanis, C. Lopez-Franco and N. Arana-Daniel, 2015. Decentralized control for stabilization of nonlinear multi-agent systems using neural inverse optimal control. Neurocomputing, 168: 81-91.
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  5. Lopez, V.G., A.Y. Alanis, E.N. Sanchez and J. Rivera, 2015. Real-time implementation of neural optimal control and state estimation for a linear induction motor. Neurocomputing, 152: 403-412.
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  6. Guillermo, J.E., L.J.R. Castellanos, E.N. Sanchez and A.Y. Alanis, 2015. Detection of heart murmurs based on radial wavelet neural network with Kalman learning. Neurocomputing, 164: 307-317.
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  7. Alanis, A.Y., J.D. Rios, J. Rivera, N. Arana-Daniel and C. Lopez-Franco, 2015. Real-time discrete neural control applied to a linear induction motor. Neurocomputing, 164: 240-251.
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  8. Leon, B.S., A.Y. Alanis, E.N. Sanchez, F. Ornelas-Tellez and E. Ruiz-Velazquez, 2014. Neural inverse optimal control via passivity for subcutaneous blood glucose regulation in type 1 diabetes mellitus patients. Intelli. Automat. Soft Comput., 20: 279-295.
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  9. Gurubel, K.J., A.Y. Alanis, E.N. Sanchez and S. Carlos-Hernandez, 2014. A neural observer with time-varying learning rate: analysis and applications. Int. J. Neural Syst., Vol. 24. 10.1142/S0129065714500117.
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  10. Alanis, A.Y., M. Hernandez-Gonzalez and E.A.Hernandez-Vargas, 2014. Observers for biological systems. Applied Soft Comput., 24: 1175-1182.
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  11. Alanis, A.Y., E.N. Sanchez and A.G. Loukianov, 2014. Real-time output trajectory tracking neural sliding mode controller for induction motors. J. Franklin Inst., 351: 2315-2334.
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  12. Alanis, A.Y., E.A. Lastire, N. Arana-Daniel and C. Lopez-Franco, 2014. Inverse optimal control with speed gradient for a power electric system using a neural reduced model. Math. Problems Eng., 10.1155/2014/514608.
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  13. Lopez-Franco, C., N. Arana-Daniel and A.Y. Alanis, 2013. Visual servoing on the sphere using conformal geometric algebra. Adv. Applied Clifford Algebras, 22: 125-141.
    Direct Link  |  

  14. Leon, B.S., A.Y. Alanis, E.N. Sanchez, F. Ornelas-Tellez and E. Ruiz-Velazquez, 2013. Neural inverse optimal control applied to type 1 diabetes mellitus patients. Analog Integrated Circuits Signal Proces., 76: 343-352.
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  15. Alanis, A.Y., L.J. Ricalde, C. Simetti and F. Odone, 2013. Neural model with particle swarm optimization Kalman learning for forecasting in smart grids. Math. Problems Eng., 10.1155/2013/197690.
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  16. Alanis, A.Y., F. Ornelas-Tellez and E.N. Sanchez, 2013. Discrete-time inverse optimal neural control for synchronous generators. Eng. Applic. Artif. Intelli., 26: 697-705.
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  17. Alanis, A.Y., E. Rangel, J. Rivera, N. Arana-Daniel and C. Lopez-Franco, 2013. Particle swarm based approach of a real-time discrete neural identifier for linear induction motors. Mathemat. Problems Eng., 10.1155/2013/715094.
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  18. Perez-Cruz, J.H., A.Y. Alanis, J.D.J. Rubio and J. Pacheco, 2012. System identification using multilayer differential neural networks: A new result. J. Applied Math., 10.1155/2012/529176.
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  19. Leon, B.S., A.Y. Alanis, E.N. Sanchez, F. Ornelas-Tellez and E. Ruiz-Velazquez, 2012. Inverse optimal neural control of blood glucose level for type 1 diabetes mellitus patients. J. Franklin Inst., 349: 1851-1870.
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  20. Leon, B.S., A.Y. Alanis, E.N. Sanchez, E. Ruiz‐Velazquez and F. Ornelas‐Tellez, 2012. Inverse optimal neural control for a class of discrete‐time nonlinear positive systems. Int. J. Adapt. Control Signal Proces., 26: 624-629.
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  21. Hernandez-Gonzalez, M., A.Y. Alanis and E.A. Hernandez-Vargas, 2012. Decentralized discrete-time neural control for a Quanser 2-DOF helicopter. Applied Soft Comput., 12: 2462-2469.
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  22. Alanis, A.Y., M. Lopez‐Franco, N. Arana‐Daniel and C. Lopez‐Franco, 2012. Discrete‐time neural control for electrically driven nonholonomic mobile robots. Int. J. Adapt. Control Signal Proces., 26: 630-644.
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  23. Alanis, A.Y., E.N. Sanchez, A.G. Loukianov and M.A. Perez, 2011. Real-time recurrent neural state estimation. IEEE Trans. Neural Networks, 22: 497-505.
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  24. Alanis, A.Y., E.N. Sanchez and A.G. Loukianov, 2011. Real-time discrete backstepping neural control for induction motors. IEEE Trans. Control Syst. Technol., 19: 359-366.
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  25. Alanis, A.Y., B.S. Leon, E.N. Sanchez and E. Ruiz-Velazquez, 2011. Blood glucose level neural model for type 1 diabetes mellitus patients. Int. J. Neural Syst., 21: 491-504.
    Direct Link  |  

  26. Alanis, Y., E.N. Sanchez, A.G. Loukianov and M.A. Perez, 2010. Discrete-time output trajectory tracking by recurrent high-order neural network control. IEEE Trans. Control Syst. Technol., 18: 11-21.

  27. Alanis, A.Y., E.N. Sanchez, A.G. Loukianov and E.A. Hernandez, 2010. Discrete-time recurrent high order neural networks for nonlinear identification. J. Franklin Inst., 347: 1253-1265.
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  28. Sanchez, E.N., A.Y. Alanis and A.G. Loukianov, 2008. Discrete-Time High Order Neural Control. Springer Verlag, Germany, Pages: 125.

  29. Alanis, A.Y., E.N. Sanchez and A.G. Loukianov, 2007. Discrete-time adaptive backstepping nonlinear control via high-order neural networks. IEEE Trans. Neural Network, 18: 1185-1195.
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  30. Sanchez, E.N. and A.Y. Alanis, 2006. Redes Neuronales. Pearson Educacion, Spain, Pages: 232, (In Spanish).
Member since September, 2017