Publicaciones en las que colabora con Julio José Ibarrola Lacalle (13)

2023

  1. Applying deep learning in brain computer interface to classify motor imagery

    Journal of Intelligent and Fuzzy Systems, Vol. 45, Núm. 5, pp. 8747-8760

2016

  1. Are low cost Brain Computer Interface headsets ready for motor imagery applications?

    Expert Systems with Applications, Vol. 49, pp. 136-144

  2. Voting Strategy to Enhance Multimodel EEG-Based Classifier Systems for Motor Imagery BCI

    IEEE Systems Journal, Vol. 10, Núm. 3, pp. 1082-1088

2015

  1. Feature selection applying statistical and neurofuzzy methods to EEG-based BCI

    Computational Intelligence and Neuroscience, Vol. 2015

2014

  1. Tuning rules for a quick start up in Dynamic Matrix Control

    ISA Transactions, Vol. 53, Núm. 2, pp. 612-627

2013

  1. How well Fuzzy ARTMAP approximates functions?

    Journal of Intelligent and Fuzzy Systems, Vol. 25, Núm. 2, pp. 335-350

2012

  1. Control loop performance assessment with a dynamic neuro-fuzzy model (dFasArt)

    IEEE Transactions on Automation Science and Engineering, Vol. 9, Núm. 2, pp. 377-389

  2. Improving motor imagery classification with a new BCI design using neuro-fuzzy S-dFasArt

    IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 20, Núm. 1, pp. 2-7

2010

  1. Applying neuro-fuzzy model dFasArt in control systems

    Engineering Applications of Artificial Intelligence, Vol. 23, Núm. 7, pp. 1053-1063

2009

  1. dFasArt: Dynamic neural processing in FasArt model

    Neural Networks, Vol. 22, Núm. 4, pp. 479-487

2008

  1. dNSP: A biologically inspired dynamic Neural network approach to Signal Processing

    Neural Networks, Vol. 21, Núm. 7, pp. 1006-1019

2007

  1. Performance monitoring of closed-loop controlled systems using dFasArt

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2006

  1. A neurofuzzy scheme to on-line identification in an adaptive-predictive control

    Neural Computing and Applications, Vol. 15, Núm. 1, pp. 41-48