Wavelet transform moments for feature extraction from temporal signals
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[1] B. Hannaford,et al. Short Time Fourier Analysis of the Electromyogram: Fast Movements and Constant Contraction , 1986, IEEE Transactions on Biomedical Engineering.
[2] Wenwei Yu,et al. EMG prosthetic hand controller using real-time learning method , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).
[3] Ying Yao,et al. An approximate degrees of freedom solution to the multivariate Behrens-Fisher problem* , 1965 .
[4] Katsunori Shimohara,et al. EMG pattern recognition by neural networks for multi fingers control , 1992, 1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[5] A. Marshall. Principles of Economics , .
[6] Han-Pang Huang,et al. Development of a myoelectric discrimination system for a multi-degree prosthetic hand , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).
[7] Ronald R. Coifman,et al. Local discriminant bases and their applications , 1995, Journal of Mathematical Imaging and Vision.
[8] P. A. Parker,et al. Improving myoelectric signal classification using wavelet packets and principal components analysis , 1999, Proceedings of the First Joint BMES/EMBS Conference. 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society (Cat. N.
[9] Dustin Boswell,et al. Introduction to Support Vector Machines , 2002 .
[10] M. I. Vuskoviv,et al. Classification of grasp modes based on electromyographic patterns of preshaping motions , 1995, 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century.
[11] H. Demsetz,et al. Production, Information Costs, and Economic Organization , 1975, IEEE Engineering Management Review.
[12] Marko Vuskovic,et al. Hierarchical discrimination of grasp modes using surface EMGs , 1996, Proceedings of IEEE International Conference on Robotics and Automation.
[13] P. A. Parker,et al. A Neural Network Classifier For Multifunction Myoelectric Control , 1991, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society Volume 13: 1991.
[14] Maryhelen Stevenson,et al. Signal representation for classification of the transient myoelectric signal , 1998 .
[15] G. Schlesinger. Der mechanische Aufbau der künstlichen Glieder , 1919 .
[16] P. A. Parker,et al. Time-frequency representation for classification of the transient myoelectric signal , 1998, Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Vol.20 Biomedical Engineering Towards the Year 2000 and Beyond (Cat. No.98CH36286).
[17] Ian D. Walker,et al. Myoelectric teleoperation of a complex robotic hand , 1996, IEEE Trans. Robotics Autom..
[18] Sijiang Du,et al. Temporal vs. spectral approach to feature extraction from prehensile EMG signals , 2004, Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, 2004. IRI 2004..
[19] Kevin B. Englehart,et al. A wavelet-based continuous classification scheme for multifunction myoelectric control , 2001, IEEE Transactions on Biomedical Engineering.
[20] R.N. Scott,et al. A new strategy for multifunction myoelectric control , 1993, IEEE Transactions on Biomedical Engineering.
[21] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[22] Nello Cristianini,et al. An introduction to Support Vector Machines , 2000 .