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G. Kitagawa, “Monte carlo filter and smoother for non-Gaussian nonlinear state space models,” Journal of Computational and Graphical Statistics, Vol. 5, No. 1, pp. 1–25, 1996.

has been cited by the following article:

• TITLE: Adaptive Method for State Estimation of Sound Environment System with Uncertainty and its Application to Psychological Evaluation

  AUTHORS: Hisako Orimoto, Akira Ikuta

  KEYWORDS: Adaptive Estimation, Sound Environment System, Uncertainty, Psychological Evaluation

  JOURNAL NAME: Intelligent Information Management, Vol.2 No.3, March 31, 2010

  ABSTRACT: The actual sound environment system exhibits various types of linear and non-linear characteristics, and it often contains uncertainty. Furthermore, the observations in the sound environment are often in the level-quantized form. In this paper, two types of methods for estimating the specific signal for sound envi-ronment systems with uncertainty and the quantized observation are proposed by introducing newly a system model of the conditional probability type and moment statistics of fuzzy events. The effectiveness of the proposed theoretical methods is confirmed by applying them to the actual problem of psychological evalua-tion for the sound environment.