Volume 9 Number 6 (Jun. 2014)
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JSW 2014 Vol.9(6): 1581-1586 ISSN: 1796-217X
doi: 10.4304/jsw.9.6.1581-1586

A Prediction Method for Underwater Acoustic Chaotic Signal Based on RBF Neural Network

Guohui Li, Hong Yang
School of Electronic and Engineering, Xi’an University of Posts and Telecommunications, Xi’an, China

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)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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