Abstract
In general, the descriptive approach on the stochastic evaluation is typically effective for the complicated situation of actual sound insulation systems with an actual random noise excitation which is impossible to evaluate by use of the well-known structual approach. In this paper, after once introducing descriptively a linear regression type system model between input and output, the system parameters have been estimated not in a sense of the usual least square error evaluation but in a sense of laying stress on the edge or the whole shape of probability distribution function. More concretely, this estimation method has been originally proposed by use of a stochastic approximation method for the purpose of extracting more effective information latent in the remainder fluctuation around the above linear regression, under a new error criterion based on equalizing a noise evaluation index L_aα and a Kullbacks information quantity for modelled and actual systems. Furthermore, in an actual case with an existence of background noise, a simplified trial of removing this background noise is also discussed. Finally, the effectiveness of the proposed evaluation methods has been experimentally confirmed too by applying it to the actually complicated sound environmental system.
