• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.969-974
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• 2007

In this paper, a beamforming technique is introduced to measure the acoustic impedance at both normal and oblique incidence in a free field. The acoustic impedance is obtained by separating incident and reflected signals using the adaptive nulling method which is one of the various beamforming algorithms. To obtain better results, pressure vector commonly used in array signal processing is replaced with the transfer function vector between each microphone and the white Gaussian noise is suppressed by a wavelet shrinkage technique. The experiments conducted in a semi-anechoic room show that the proposed method is efficient and accurate in measuring the acoustic impedance of sound absorbing materials under a free field condition.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.135-138
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• 2001

Many researchers have developed the techniques of an efficient 3-D sound system based on the psycho-acoustics of spatial hearing with multimedia or virtual reality In this paper, we propose an idea for the improved 3-D sound system using conventional stereo headphones to obtain a better sound diffusion from the mono-sound recorded at an anechoic chamber. We use the HRTF (Head Related Transfer Function) for the sound localization and the wavelet filter bank with time delay for the sound diffusion. We investigate the effects of the 3-B sound depending on the length of time delay at lowest frequency band. Also the correlation coefficient of the signals between the left channel and the right channel is measured to identify the sound diffusion.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.4
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• pp.23-29
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• 2003

In this paper, we propose an idea for the improved 3-D sound system using conventional stereo headphones to obtain a better sound diffusion from the mono-sound recorded at an anechoic chamber. We use the HRTF(Head Related Transfer Function) for the sound localization and the wavelet filter bank with time delay for the sound diffusion. And we test the modified HRTF with the various sampling rate. We investigate the effects of the 3-D sound depending on the length of time delay at lowest frequency band. Also the correlation coefficient of the signals between the left channel and the right channel is measured to identify the sound diffusion. At last we obtain the diffusion sound using Cool Edit for reverberation.

• Journal of the Korean Society of Radiology
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• v.3 no.1
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• pp.29-39
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• 2009

In this paper has proposed to the recognition of the disease on medical images using neural network. The neural network is constructed as three-layers of the input-layer, the hidden-layer and the output-layer. The training method applied for the recognition of disease region is adaptive error back-propagation. The low-frequency region analyzed by DWT are expressed by matrix. The coefficient-values of the characteristic polynomial applied are n+1. The normalized maximum value +1 and minimum value -1 in the range of tangent-sigmoid transfer function are applied to be use as the input vector of the neural network. To prove the validity of the proposed methods used in the experiment with a simulation experiment, the input medical image recognition rate the evaluation of areas of disease. As a result of the experiment, the characteristic polynomial coefficient of low-frequency area matrix, conversed to 4 level DWT, was proved to be optimum to be applied to the feature parameter. As for the number of training, it was marked fewest in 0.01 of learning coefficient and 0.95 of momentum, when the adaptive error back-propagation was learned by inputting standardized feature parameter into organized neural network. As to the training result when the learning coefficient was 0.01, and momentum was 0.95, it was 100% recognized in fifty-five times of the stomach image, fifty-five times of the chest image, forty-six times of the CT image, fifty-five times of ultrasonogram, and one hundred fifty-seven times of angiogram.