Sound pressure level (SPL) measurements were performed on a controlled test track vehicle coast-by runs of a passenger vehicle with six different sets of tires across a range of temperatures. A small but significant reduction of noise level with positive temperature increases was observed for some tires. The temperature gradient of the different tires at 80㎞/h ranged from -0.07 to + 0.01 dB/℃. Frequency analysis of the tire noise identified that noise content in the range of 1,300 to 1,900Hz was particularly sensitive to temperature changes. Differences in SPL due to speed and tire type were much greater than that due to temperature.

In this paper we propose a new subspace tracking algorithm based on the PASTd (Projection Approximation Subspace Tracking with deflation). The algorithm is obtained via introducing the variable forgetting factor which adapts itself to the time-varying subspace environments. The tracking capability of the proposed algorithm is demonstrated by computer simulations in an abruptly changing DOA scenario. The estimation results of the variable forgetting factor PASTd(VFF-PASTd) outperform those of the PASTd in the nonstationary case as well as in the stationary case.

We have proposed BIST method and circuit for embedded 16M SDRAM with logic. It can test the AC parameter of embedded 16M SDRAM using the BIST circuit capable of detecting the address of a fail cell installed in an Merged Memory with Logic(MML). It generates the information of repair for redundancy circuit. The function and AC parameter of the embedded memory can also be tested using the proposed BIST method. It is possible to test the embedded SDRAM without external test pin. The total gate of the BIST circuit is approximately 4,500 in the case of synthesizing by 0.25μm cell library and is verified by Verilog simulation. The test time of each one AC parameter is about 200ms using 2Y-March 14n algorithm.

We propose the computation reduction method of real root method that is mainly used in the CELP(Code Excited Linear Prediction) vocoder. The real root method is that if polynomial equations have the real roots, we are able to find those and transform them into LSF[1]. However, this method takes much time to compute, because the root searching is processed sequentially in frequency region. But, the important characteristic of LSF is that most of coefficients are occurred in specific frequency region. So, the searching frequency region is ordered by each coefficient's distribution. And coefficients are searched in ordered frequency region. Transformation time can be reduced by this method than the sequential searching method in frequency region. When we compare this proposed method with the conventional real root method, the experimental result is that the searching time was reduced about 46% in average.

The unstable signature that is defined as frequency change with respect to the time or frequency modulation, is caused by the external loading variation in specific machinery component and Doppler shift etc. In this study, we analyze the generation mechanism of the unstable signature and apply the Extended Kalman filter (EKF) algorithm for its detection. The performance of Extended Kalman Filter is examined for numerical and measured signals and the results show its validity for unstable signature detection.

Matched Field Processing (MFP) is a successive process of correcting mismatches between true and assumed parameters by matching the measured acoustic field data with numerically simulated data which we call replica. The MFP is widely used both in geo-acoustic parameter inversions and in source localizations. Whether a certain parameter can be inverted effectively or whether a source can be localized correctly depends on the amount of the influence that a parameter has on the acoustic field during the matching process. Sensitive parameters can be better estimated than the less sensitive ones in MFP. On the contrary, the sensitive parameters affect adversely on the source localization results when they have uncertainties. In this paper, a sensitivity index is defined based upon the field variation resulting from the perturbed parameters. Numerical test results show that the index behaves in accordance with the results of source localization under a mismatched environment and also with the inversion solutions.