Akira Ikuta

Evaulation method for complex sound environment system under unknown structure and existence of observation noise

The actual sound environment system exhibits various types of linear and non-linear characteristics, and it often contains an unknown structure. Furthermore, the processes observed in the sound environment inevitably contain observation noise or uncertain factors. In this paper, a method for estimating the specific signal for a sound environment system with unknown structure and observation noise of unknown statistical property is proposed by introducing a system model of the conditional probability type. The effectiveness of the proposed theoretical method is confirmed by applying it to the actual problem of signal estimation of the sound environment.

Estimation of several types of correlation information between sound and electromagnetic waves leaked from VDT environment based on the introduction of fuzzy probability and the prediction of probability distribution

In this paper, a signal processing method considering not only linear correlation but also the higher order nonlinear correlation information is proposed on the basis of fuzzy observation data, in order to find the mutual relationship between sound and electromagnetic waves leaked from an electronic information equipment. More specifically, by applying the well-known fuzzy probability to an expression on the multi-dimensional probability distribution in an orthogonal expansion series form reflecting systematically various types of correlation information, a method to estimate precisely the correlation information between the variables from the conditional moment statistics of fuzzy variables is proposed. The effectiveness of the proposed theory is experimentally confirmed by applying it to the observation data leaked from VDT in the actual work environment.

An improvement of restoration method using digital filter for medical X-ray images contaminated by quantum mottles with varying variance

A novel restoration method for X-ray images with quantum mottles is proposed by considering the physical formation process of X-ray images. More specifically, as a restoration method for quantum mottles, a digital filter of the stochastic type considering the property of quantum mottles with varying variance is derived on the basis of the Bayes theorem matched to recursive image processing. In order to confirm the effectiveness of the proposed method, it is applied to an actual medical image.<<ETX>>

A Methodological Trial in the Hierarchical Form of Kalman Filter and a State Estimation in the Room Acoustical Field

In the actual random phenomena, the objective signal usually shows a complex fluctuation pattern apart from a standard Gaussian distribution due to the diversified causes of fluctuation. Furthermore, the observation data are very often contaminated by the external noise of arbitrary distribution type. In this paper, a new state estimation algorithm for the stochastic system with a random excitation of non-Gaussian distribution type is proposed by introducing a form of expansion expression with parameter differential type for the conditional probability density function. It is noticeable that the proposed wide sense digital filter is constructed in a hierarchical form based on the direct use of the well-known Kalmans filtering algorithm. Therefore, non-Gaussian properties of the fluctuation and various nonlinear correlation information are reflected hierarchically in this estimation algorithm. Finally, the effectiveness of the theory is experimentally confirmed too by applying it to the actual data in the room acoustical field.