Haiping Lu

Summary

Affiliation: University of Toronto
Country: Canada

Publications

  1. doi request reprint Regularized common spatial patterns with generic learning for EEG signal classification
    Haiping Lu
    Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON M5S3G4, Canada
    Conf Proc IEEE Eng Med Biol Soc 2009:6599-602. 2009
  2. doi request reprint Uncorrelated multilinear discriminant analysis with regularization and aggregation for tensor object recognition
    Haiping Lu
    Edward S Rogers Sr Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON M5S 3G4 Canada
    IEEE Trans Neural Netw 20:103-23. 2009
  3. doi request reprint MPCA: Multilinear Principal Component Analysis of Tensor Objects
    Haiping Lu
    Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON M5S 3G4, Canada
    IEEE Trans Neural Netw 19:18-39. 2008

Detail Information

Publications3

  1. doi request reprint Regularized common spatial patterns with generic learning for EEG signal classification
    Haiping Lu
    Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON M5S3G4, Canada
    Conf Proc IEEE Eng Med Biol Soc 2009:6599-602. 2009
    ..5% on average. Moreover, the regularization introduced is particularly effective in the small-sample setting...
  2. doi request reprint Uncorrelated multilinear discriminant analysis with regularization and aggregation for tensor object recognition
    Haiping Lu
    Edward S Rogers Sr Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON M5S 3G4 Canada
    IEEE Trans Neural Netw 20:103-23. 2009
    ....
  3. doi request reprint MPCA: Multilinear Principal Component Analysis of Tensor Objects
    Haiping Lu
    Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON M5S 3G4, Canada
    IEEE Trans Neural Netw 19:18-39. 2008
    ..It is shown that even without a fully optimized design, an MPCA-based gait recognition module achieves highly competitive performance and compares favorably to the state-of-the-art gait recognizers...