Intelligent Information Management

Volume 11, Issue 6 (November 2019)

ISSN Print: 2160-5912   ISSN Online: 2160-5920

Google-based Impact Factor: 0.89  Citations  h5-index & Ranking

State Estimation for Sound Environment System with Nonlinear Observation Characteristics by Introducing Wide-Sense Particle Filter

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DOI: 10.4236/iim.2019.116008    113 Downloads   234 Views  

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.

Cite this paper

Orimoto, H. , Ikuta, A. and Hasegawa, K. (2019) State Estimation for Sound Environment System with Nonlinear Observation Characteristics by Introducing Wide-Sense Particle Filter. Intelligent Information Management, 11, 87-101. doi: 10.4236/iim.2019.116008.

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