A Probabilistic Evaluation Method of Output Response Based on the Extended Regression Analysis Method for Sound Insulation Systems with Roughly Observed Data

Noboru NAKASAKO  Mitsuo OHTA  Yasuo MITANI  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E80-A   No.8   pp.1410-1416
Publication Date: 1997/08/25
Online ISSN: 
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Digital Signal Processing)
quantized-level observations,  Bayes' theorem,  extended regression analysis,  joint probability density function,  output response probability distribution,  

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In this paper, a new trial for the signal processing is proposed along the same line as a previous study on the extended regression analysis based on the Bayes' theorem. This method enables us to estimate a response probability property of complicated systems in an actual case when observation values of the output response are roughly observed due to the quantization mechanism of measuring equipment. More concretely, the main purpose of this research is to find the statistics of the joint probability density function before a level quantization operation which reflects every proper correlation informations between the system input and the output fluctuations. Then, the output probability distribution for another kind of input is predicted by using the estimated regression relationship. Finally, the effectiveness of the proposed method is experimentally confirmed by applying it to the actually observed input-output data of the acoustic system.