| 小波神经网络研究进展及展望 |
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| 引用本文： | 陈哲,冯天瑾.小波神经网络研究进展及展望[J].中国海洋大学学报(自然科学版),1999(4). |
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| 作者姓名： | 陈哲 冯天瑾 |
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| 作者单位： | 青岛海洋大学电子工程系!青岛，266003，青岛海洋大学电子工程系!青岛，266003 |
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| 摘 要： | 关于小波分析与人工神经网络结合的研究，近些年来已成为信号处理学科的热点之一，已有大量的研究成果见诸各种学术刊物和会议论文。小波变换具有良好的时频局部性质，神经网络则具有自学习功能和良好的容错能力，小波神经网络（ＷＮＮ）由于较好地结合了两者的优点而具有强大的优势。作者较系统地综述了小波神经网络的研究进展，讨论了小波神经网络的主要模型和算法，并就其存在的一些问题，应用与发展趋势进行了探讨
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| 关 键 词： | 神经网络 小波分析 小波神经网络 |
Research Developments and Prospects of Wavelet Neural Networks |
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| Chen Zhe,Feng Tianjin.Research Developments and Prospects of Wavelet Neural Networks[J].Periodical of Ocean University of China,1999(4). |
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| Authors: | Chen Zhe Feng Tianjin |
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| Abstract: | Wavelet neural networks (WNN) have attracted much attention recently, and a considerable number of theory and application achievements have appeared in va rious publications. Wavelet transform has the exceptional property of temporal frequency localization, whereas neural networks have excellent characteristics of self learning and fault tolerance. By combining their good merits, WNN have shown more powerful competence. The advances and developments of this field are reviewed in this paper. WNN, including its main models and algorithms, are stressed particularly. Some concerns and applications about WNN are also introduced. Finally we discuss the research trend and the prospects. |
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| Keywords: | neural networks wavelet analysis wavelet neural networks (WNN) |
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