Fuzzy Bayesian Filter for Sound Environment by Considering Additive Property of Energy Variable and Fuzzy Observation in Decibel Scale

A. Ikuta, H. Orimoto
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Abstract

In the measurement and evaluation of actual random signal in a sound environment, the observed data often contain the fuzziness due to several causes. Furthermore, there exists usually a background noise in addition to the objective specific signal, and it is often that the specific signal partly or completely is buried in the background noise. In this paper, a fuzzy Bayesian filter for estimating a specific signal, based on the observed data containing the fuzziness, and the effects of a background noise with non-Gaussian type is proposed. More specifically, after paying attention to the energy variables satisfying the additive property of the specific signal and background noise, by introducing a new type of membership function suitable for the energy variable and the observation in decibel scale, a state estimation method is theoretically derived. The proposed theory is applied to the actual estimation problem of the sound environment, and its usefulness is experimentally verified.
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考虑能量变量可加性和分贝尺度模糊观测的声环境模糊贝叶斯滤波
在声环境中实际随机信号的测量和评价中,由于多种原因,观测数据往往具有模糊性。此外,除了客观的特定信号外,通常还存在背景噪声,并且通常特定信号部分或全部被淹没在背景噪声中。本文基于观测数据的模糊性和非高斯型背景噪声的影响,提出了一种用于估计特定信号的模糊贝叶斯滤波器。更具体地说,在关注满足特定信号和背景噪声加性的能量变量后,通过引入一种适合于能量变量和分贝尺度观测值的新型隶属函数,从理论上推导出一种状态估计方法。将该理论应用于声环境的实际估计问题,并通过实验验证了其有效性。
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