A Recurrent Probabilistic Neural Network for EMG Pattern Recognition

In the field of pattern recognition, probabilistic neural networks (PNNs) have been proven as an important classifier. For pattern recognition of EMG signals, the characteristics usually used are: (1) amplitude, (2) frequency, and (3) space. However, significant temporal characteristic exists in the transient and non-stationary EMG signals, which cannot be considered by traditional PNNs. In this article, a recurrent PNN, called IDEA GROUP PUBLISHING This paper appears in the publication, Neural Networks in Healthcare: Potential and Challenges edited by Rezaul Begg, Joarder Kamruzzaman, and Ruhul Sarker © 2006, Idea Group Inc. 701 E. Chocolate Avenue, Suite 200, Hershey PA 17033-1240, USA Tel: 717/533-8845; Fax 717/533-8661; URL-http://www.idea-group.com ITB12178

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