A recurrent fuzzy filter for the analysis of lung sounds

被引:6
|
作者
Mastorocostas, PA [1 ]
机构
[1] Technol Educ Inst Serres, Dept Informat & Commun, Serres 62124, Greece
关键词
discontinuous adventitious sounds; vesicular sounds; recurrent fuzzy-neural modeling; orthogonal least squares; TSK fuzzy rules; dynamic neurons;
D O I
10.1016/j.fss.2005.06.020
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
This paper presents a recurrent fuzzy-neural filter for real-time separation of discontinuous adventitious sounds from vesicular sounds. The filter uses two dynamic neuron-based fuzzy neural networks to perform the task of separation. The networks are generated by the dynamic orthogonal least-squares method and are applied to all kinds of lung sounds. Extensive experimental results are given and a performance comparison with a series of other models is conducted, underlining the effectiveness of the proposed filter and its superior performance over its competing rivals. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:578 / 594
页数:17
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