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Volume 21 Issue 5
Sep.  1999
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Yang Su, Li Zhishun. USING ITERATED FUNCTION SYSTEM BASED ON NEURAL NETWORK TO MODEL TIME SEQUENCES[J]. Journal of Electronics & Information Technology, 1999, 21(5): 619-623.
Citation: Yang Su, Li Zhishun. USING ITERATED FUNCTION SYSTEM BASED ON NEURAL NETWORK TO MODEL TIME SEQUENCES[J]. Journal of Electronics & Information Technology, 1999, 21(5): 619-623.

USING ITERATED FUNCTION SYSTEM BASED ON NEURAL NETWORK TO MODEL TIME SEQUENCES

  • Received Date: 1998-02-09
  • Rev Recd Date: 1998-10-23
  • Publish Date: 1999-09-19
  • A new method to resolve fractal inverse problem based on neural network was presented in this paper which can be employed to model a time sequences.The precondition to assure the model was also provided. A piece of echo from a lake was taken to test the algorithm. The result is satisfying.
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  • Barnsley M F, Demko S. Iterated function system and the global construction of fractals. Proc. Roy. Soc. London, 1985, A-399(1817): 243-275.[2] Mazel D S, Hayes M H. Using iterated function system to model discrete sequences. IEEE Trans. on SP, 1992, SP-40(7): 1724-1734.[2]赵耀,袁保宗. 一种基于新仿射变换的分形序列图像编码方法. 电子学报,1997, 25(7): 28-31.[3]谢和平, 薛秀谦. 分形应用中的数学基础与方法. 北京: 科学出版社,1997, 27-40, 99-106, 170-175.[4]Hecht-Nielsen R. Theory of the backpropagation neural network. IJCNN, San Diego: 1989, 1, 593-605.[5]罗发龙, 李衍达. 神经网络信号处理. 北京: 电子工业出版社, 1993, 7-7.
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