Soft Computing Based Signal Prediction, Restoration, and Filtering

  • Eiji Uchino
  • Takeshi Yamakawa


In this chapter, soft computational signal processing, especially devoted to prediction, restoration and filtering of signals, is discussed. The neo-fuzzy-neuron, developed by the authors, are applied to the prediction and restoration of damaged signals. The chaotic signals and the speech signals are employed for the experiments. The filtering of noisy signals based on the Radial Basis Function (RBF) network, a special class of a fuzzy neural network, is also discussed. The proposed filter can eliminate not only Gaussian noise but also noise with an arbitrary distribution.


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Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Eiji Uchino
    • 1
  • Takeshi Yamakawa
    • 1
  1. 1.Dept of Computer Science and Control EngineeringKyushu Institute of TechnologyIizuka, FukuokaJapan

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