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( Talcahiro Sato ),( Katsu Yamazaki ),( Jouji Toyota ),( Yoshiyasu Karino ),( Takumi Ohmura ),( Toshihim Suga ) 대한소화기학회 2007 SIDDS Vol.9 No.-
Background/Aims: We evaluated hemodynamics of esophageal varices that were resistant to endoscopic injection sclerotherapy (EIS) Using 5% ethanolamine oleate with iopamidol (5% EOI) and in need of EIS using absolute alcohol (AA). Methods: Consecutive 490 patients who underwent hemodynamic evaluation using endoseopic color Doppler ultrasonography (ECDUS) and ultrasonic microprobe (UMP) were studied. Results: Nine patients were resistant to EIS using 5% EOI and the additional use of AA in this group was performed (AA group). Various parameters were compared between the 481 patients who had been administered EIS using 5% EOI (EO group) and the 9 patients in AA group. The mean number of EIS treatments in the AA group (6.8±3.4) was significantly greater than in the EO group (4.4±2.1 times) (p<0.01). The mean amount of 5% EOI provided in the AA group (31.1±17.4 mL) was significantly larger than in the EO group (14.9±8.8 mL) (P<0.001). The mean velocity of esophageal varices in the AA group (13.6±3.2 cm/s) was significantly higher than in the EO group (9.4±3.1 cm/s) (P<0.001) determined by ECDUS. The mean diameter of esophageal varices as found by UMP was 8.0±3.5 mm in the AA group and 4.6±2.4 mm in the EO group, with the difference being significant (p<0.01). The mean diameter of the perforating vein was 3.8±1.9 mm in the AA group and 2.1±0.5 mm in the EO group as shown by UMP, a difference that was statistically significant (p<0.01). Conclusions: Hemodynamic evaluation revealed that the esophageal varices were more severe in the AA group than in the EO group.
Gradient-Type Instrumental Variable Method and Its Application to Channel Equalization
Shimamura, Tetsuya,Suzuki, Jouji,Takada, Tomoyuki 대한전자공학회 1994 ISPACS:Intelligent Signal Processing and Communica Vol.1 No.1
In this paper, we present an adaptive IIR equalizer using system identification techniques. Gradient-type instrumental variable(GIV) algorithm is used for the purpose of channel estimation. The proposed equalizer has a cascade structure of an ARMA prefilter and an adaptive FIR equalizer. The ARMA prefilter is designed based on the transfer function estimated by the GIV algorithm. The ARMA prefiltering leads to reduction in a degree of correlation of the channel output. The LMS algorithm of the cascaded FIR adaptive equalizer provides faster convergence and smaller residual errors than the commonly used adaptive FIR equalizer. Simulation results are shown to confirm the performance of the proposed adaptive IIR equalizer.