Pulse images recognition using fuzzy neural network

Authors:
Lisheng Xu;Max Q. -H. Meng;Kuanquan Wang;Wang Lu;Naimin Li
Affiliations:
Department of Electronic Engineering, Room 206, Ho Sin Hang Engineering Building, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong and School of Control Science and Engineering, Shando ...;Department of Electronic Engineering, Room 206, Ho Sin Hang Engineering Building, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong;Department of Computer Science and Engineering, Harbin Institute of Technology, Harbin 150001, China;Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong;No. 211 Hospital, Harbin 150080, China
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Abstract

The automatic recognition of pulse images is the key in the research of computerized pulse diagnosis. In order to automatically differentiate the pulse patterns by using small samples in pulse diagnosis, a fuzzy neural network for classifying pulse images based on the knowledge of experts in traditional Chinese pulse diagnosis was designed. The designed classifier can make hard decision and soft decision for identifying 16 patterns of pulse images at the accuracy of 90.25%, which is better than the results that are achieved by back propagation neural network.