doi: 10.4304/jsw.9.6.1581-1586
A Prediction Method for Underwater Acoustic Chaotic Signal Based on RBF Neural Network
Abstract—In this paper, the chaotic time series RBF neural network model was designed. A prediction method for underwater acoustic chaotic signal based on RBF neural network is proposed in this paper according to the characteristics of chaotic signal with the short-term prediction. Typical Henon chaotic signal and the actual underwater acoustic chaotic signal are respectively predicted by the RBF neural network. Then the prediction results are analyzed. The results show that the proposed prediction method increases at least two orders of magnitude in the mean square error terms compared with existing prediction method, and that the RBF neural network can be used to predict the chaotic signal effectively.
Index Terms—chaotic signal, phase space reconstruction, RBF neural network, prediction
Cite: Guohui Li, Hong Yang, "A Prediction Method for Underwater Acoustic Chaotic Signal Based on RBF Neural Network," Journal of Software vol. 9, no. 6, pp. 1581-1586, 2014.
General Information
ISSN: 1796-217X (Online)
Abbreviated Title: J. Softw.
Frequency: Biannually
APC: 500USD
DOI: 10.17706/JSW
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Cecilia Xie
Abstracting/ Indexing: DBLP, EBSCO,
CNKI, Google Scholar, ProQuest,
INSPEC(IET), ULRICH's Periodicals
Directory, WorldCat, etcE-mail: jsweditorialoffice@gmail.com
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