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Ikuta, A. and Orimoto, H. (2014) Static and Dynamic Methods for Fuzzy Signal Processing of Sound and Electromagnetic Environment Based on Fuzzy Observations. In: Merelo, J.J., et al., Eds., Computational Intelligence, Studies in Computational Intelligence, Vol. 620, Springer, Berlin, 171-187.

has been cited by the following article:

• TITLE: State Estimation for Fuzzy Sound Environment System with Finite Amplitude Fluctuation

  AUTHORS: Akira Ikuta, Hisako Orimoto, Gerard Gallagher

  KEYWORDS: Fuzzy Observation, Sound Environment System, Finite Fluctuation Range, State Estimation

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.10 No.7, June 23, 2017

  ABSTRACT: Internal physical mechanism of actual sound environment system is often difficult to recognize analytically, and it contains unknown structural characteristics. Furthermore, the observation data often contain fuzziness due to several causes and exhibit level saturation owing to the existence of a finite dynamic range. Therefore, it is necessary to propose a new state estimation method by considering fuzziness and finite amplitude fluctuation of observation data. In this paper, a method for estimating the specific signal for sound environment system with unknown structure is proposed in an appropriate form for the finite level range of the measured fuzzy observation data by introducing an expansion expression of probability distribution with Bata distribution in the first term and new type of membership function. The effectiveness of the proposed theoretical method is confirmed by applying it to the actual problem in the sound environment.