Abstract
In this study, a modified particle filter considering non-Gaussian properties of noises is proposed in a form applicable to real situation in sound environment system where the observation data are contaminated by the external noise (i.e., background noise) of arbitrary probability distribution and measured in decibel scale. More specifically, a nonlinear observation model in decibel scale with a quantized level is first paid considered by introducing the additive property of energy variables (i.e., sound intensity) in sound environment system. Next, a wide-sense particle filter of an expansion expression type is derived in a form suitable for the nonlinear observation characteristics and the signal processing considering higher-order correlation information between the specific signal and observation. Furthermore, the effectiveness of the proposed theory is confirmed by applying it to the observed data measured in real sound environment.
Highlights
In the real sound environment system, the observed data contains the effect of several fluctuation factors such as noises in addition to the specific signal
A modified particle filter considering non-Gaussian properties of noises is proposed in a form applicable to real situation in sound environment system where the observation data are contaminated by the external noise of arbitrary probability distribution and measured in decibel scale
The background noise usually exists in real sound environment system and the effect of the background noise often has to be eliminated in order to evaluate the sound environment system
Summary
In the real sound environment system, the observed data contains the effect of several fluctuation factors such as noises in addition to the specific signal. We often encounter the situation necessary to estimate reasonably only the specific signal based on the observed data by introducing some signal
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