Jose Principe

Jose C. Principe is a Distinguished Professor of electrical and computer engineering and biomedical engineering at the University of Florida where he teaches advanced signal processing,machine learning, and artificial neural networks (ANNs) modeling. He is a BellSouth Professor and the Founder and Director of the University of Florida Computational NeuroEngineering Laboratory (CNEL). His primary area of interest is processing of time-varying signals with adaptive neural models. The CNEL has been studying signal and pattern recognition principles based on information-theoretic criteria (entropy and mutual information). He is an IEEE Fellow. He is a Member of the ADCOM of the IEEE Signal Processing Society, a Member of the Board of Governors of the International Neural Network Society, and the Editor-in-Chief of the IEEE Transactions on Biomedical Engineering. He is a Member of the Advisory Board of the University of Florida Brain Institute. He has more than 90 publications in refereed journals, 10 book chapters, and 200 conference papers. He directed 35 Ph.D. dissertations and 45 Master theses. He recently wrote an interactive electronic book entitled Neural and Adaptive Systems: Fundamentals Through Simulation published by John Wiley and Sons.

Biography Updated on 23 March 2005

Articles in Scholarly Journals [Incomplete List]

  1. Kernel Affine Projection Algorithms
    EURASIP Journal on Advances in Signal Processing, vol. 2008, Article ID 784292, 12 pages, 2008
  2. Clustering Approach to Quantify Long-Term Spatio-Temporal Interactions in Epileptic Intracranial Electroencephalography
    Computational Intelligence and Neuroscience, vol. 2007, Article ID 83416, 18 pages, 2007
  3. Simulation of Human Speech Production Applied to the Study and Synthesis of European Portuguese
    EURASIP Journal on Applied Signal Processing, vol. 2005, no. 9, pp. 1435–1448, 2005
  4. Determining Patterns in Neural Activity for Reaching Movements Using Nonnegative Matrix Factorization
    EURASIP Journal on Applied Signal Processing, vol. 2005, no. 19, pp. 3113–3121, 2005
  5. Recursive Principal Components Analysis Using Eigenvector Matrix Perturbation
    EURASIP Journal on Applied Signal Processing, vol. 2004, no. 13, pp. 2034–2041, 2004
  6. Simultaneous Principal-Component Extraction with Application to Adaptive Blind Multiuser Detection
    EURASIP Journal on Applied Signal Processing, vol. 2002, no. 12, pp. 1473–1484, 2002