doi: 10.4304/jsw.9.6.1581-1586
A Prediction Method for Underwater Acoustic Chaotic Signal Based on RBF Neural Network
- School of Electronic and Engineering, Xi’an University of Posts and Telecommunications, Xi’an, China
Abstract
In this paper, the chaotic time series RBF neuralnetwork model was designed. A prediction method forunderwater acoustic chaotic signal based on RBF neuralnetwork is proposed in this paper according to thecharacteristics of chaotic signal with the short-termprediction. Typical Henon chaotic signal and the actualunderwater acoustic chaotic signal are respectivelypredicted by the RBF neural network. Then the predictionresults are analyzed. The results show that the proposedprediction method increases at least two orders ofmagnitude in the mean square error terms compared withexisting prediction method, and that the RBF neuralnetwork can be used to predict the chaotic signal effectively.
Keywords
- chaotic signal
- phase space reconstructi
How to Cite
Guohui Li and 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. https://doi.org/ 10.4304/jsw.9.6.1581-1586
Copyright & License
Copyright © 2014 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).