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

机译:模糊贝叶斯过滤器通过考虑分贝尺度的能量变量和模糊观察的添加性能

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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.
机译:在声音环境中的实际随机信号的测量和评估中,观察到的数据通常包含由于若干原因而导致的模糊性。此外,除了物镜特定信号之外,通常还存在背景噪声,并且通常在背景噪声中掩埋特定信号部分或完全被掩埋。本文基于包含模糊性的观察数据,提出了一种用于估计特定信号的模糊贝叶斯滤波器,以及用非高斯类型的背景噪声的效果。更具体地,在注意满足特定信号和背景噪声的能量变量的能量变量之后,通过引入适合于能量变量的新类型的隶属函数和分贝标尺的观察,理论上衍生出状态估计方法。建议的理论应用于声音环境的实际估计问题,其有用性是通过实验验证的。

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