首页 | 本学科首页   官方微博 | 高级检索  
     

小波分析与神经网络结合的研究进展
引用本文:陈哲,冯天瑾.小波分析与神经网络结合的研究进展[J].电子与信息学报,2000,22(3):496-504.
作者姓名:陈哲  冯天瑾
作者单位:青岛海洋大学电子工程系,青岛海洋大学电子工程系 青岛 266003,青岛 266003
基金项目:国家自然科学基金(69675005)
摘    要:目前,小波与神经网络的结合是一个十分活跃的研究领域。本文综述了这一领域的研究进展和现状,从两者结合方式的不同将其分为辅助式及嵌套式两种结合方式,重点阐述了嵌套式的结合方式小波神经网络,并对其主要模型、算法和其它相关问题进行了论述。本文还讨论了小波网络的各种应用,从中可以看到它在函数逼近、信号分类、系统辨识、图像压缩等应用领域有极大的潜力,最后展望了今后的研究方向。

关 键 词:神经网络    小波    小波网络
收稿时间:1998-10-5
修稿时间:1999-5-23

RESEARCH ADVANCES ON COMBINATIN OF WAVELET ANALYSIS AND NEURAL NETWORKS
Chen Zhe,Feng Tianjin.RESEARCH ADVANCES ON COMBINATIN OF WAVELET ANALYSIS AND NEURAL NETWORKS[J].Journal of Electronics & Information Technology,2000,22(3):496-504.
Authors:Chen Zhe  Feng Tianjin
Affiliation:Chen Zhe Feng Tianjin (Ele.ctricdl Engineering Department. Ocean University of Qinydao. Qingdao 266003) Chen Zhe Feng Tianjin (Ele.ctricdl Engineering Department. Ocean University of Qinydao. Qingdao 266003)
Abstract:In recent years,the researches on combination of wavelet analysis and neural networks have attracted much attention. This paper reviews the development and status about, this field. The combination of wavelet and neural networks can be categorized into the ancillary type and the embedded type, the latter of which is referred to wavelet neural nctworks(WNN). WNN including its main models, algorithms and other issues are discussed. The applications and prospects of WNN are also given, which showed that WNN have great competence and potential in the applications of function approximation, signal classification,system identification and image compression.
Keywords:Neural networks  Wavelet  Wavelet networks  
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《电子与信息学报》浏览原始摘要信息
点击此处可从《电子与信息学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号