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

来源：

FUZZY SETS AND SYSTEMS | 2006年 / 157卷 / 04期

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

页码：578 / 594

页数：17

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