• Journal of the Korea Convergence Society
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• v.8 no.5
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• pp.13-17
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• 2017

Existing Speech feature extracting method in speech Signal, there are incorrect recognition rates due to incorrect speech which is not clear threshold value. In this article, the modeling method for improving speech recognition performance that combines the feature extraction for speech and silence characteristics normalized to the non-speech. The proposed method is minimized the noise affect, and speech recognition model are convergence of speech signal feature extraction to each speech frame and the silence feature normalization. Also, this method create the original speech signal with energy spectrum similar to entropy, therefore speech noise effects are to receive less of the noise. the performance values are improved in signal to noise ration by the silence feature normalization. We fixed speech and non speech classification standard value in cepstrum For th Performance analysis of the method presented in this paper is showed by comparing the results with CHMM HMM, the recognition rate was improved 2.7%p in the speech dependent and advanced 0.7%p in the speech independent.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.173-175
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• 2014

In this paper, we compare a bit error rate performance with channel estimation for terrestrial cloud transmission systems in order to provide an advanced research. Since terrestrial cloud transmission systems experience co-channel interference from one or more transmitters, they have to operate under negative signal-to-noise ratio.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.2
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• pp.80-87
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• 1994

Fetal monitoring is a routine procedure to obtain a record of physiologic functions during pregnancy and labor. It is required to determine fetal heart frequency accurately. There are various types of fetal heart rate(FHR) determination and the most frequently applied method is transabdominal Doppler ultrasound. However, in the case of weak or noise corrupted Doppler ultrasound signals, conventional peak detections and the autocorrelation function method have many difficulties to determine FHR precisely. Also the autocorrelation function is effected by threshold level and window size. To solve these problems, the high resolution pitch determination algorinthm is introduced to detect FHR from Doppler ultrasound signals. This scheme digitally processes Doppler ultrasound signal for digital rectification, envelope detection, decimation and correlation calculation of two interconnected segments and then FHR is determined by its maximal value. Even in the case of a greatly smeared noise signal, this algorithm is able to search FHR more accurately than autocorrelation function by means of compensating FHR with a constant correlation threshold. This algorithm is simulated by 386-MATLAB on PC 486/DX and verified that it is superior to the autocorrelation function method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.8
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• pp.1421-1432
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• 1994

The optimum design and performance of noncoherent TDL considering the effect of distortions due to the IF bandpasss filters are described. NRZ data and ideal filter is presumed in the simulation. The optimum filter bandwidth is calculated in the sense of minimizing the loop's squaring loss, which is equivalent to minimizing the loop's tracking jitter for a given data rate and data signal-to-noise ratio. As a result, the optimum filter bandwidth depends on the signal-to-noise ratio, and is obtained in the range of about 1-2 times of the data rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.6C
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• pp.384-390
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• 2011

The paper derives formulas for the mean-squared error distortion and resulting signal-to-noise (SNR) ratio of a fixed-rate scalar quantizer designed optimally in the minimum mean-squared error sense for a Gaussian density with the standard deviation ${\sigma}_q$ when it is mismatched to a Laplacian density with the standard deviation ${\sigma}_q$. The SNR formulas, based on the key parameter and Bennett's integral, are found accurate for a wide range of $p\({\equiv}\frac{\sigma_p}{\sigma_q}\){\geqq}0.25$. Also an upper bound to the SNR is derived, which becomes tighter with increasing rate R and indicates that the SNR behaves asymptotically as $\frac{20\sqrt{3{\ln}2}}{{\rho}{\ln}10}\;{\sqrt{R}}$ dB.

• Korean Journal of Optics and Photonics
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• v.13 no.6
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• pp.486-492
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• 2002

In this paper. we presented 1 & 2 dimensional minimum mean-squared-error (MMSE) equalization scheme in a digital holographic data storage system to improve bit-error-rate (BER) and to mitigate inter-symbol interference (ISI) which were generated during the data storage and retrieval processes. We showed experimentally for ten data pages retrieved from the holographic storage system that BER and signal-to-noise ratio (SNR) were improved by adopting MMSE equalization.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.497-500
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• 2000

In this paper, we compare the bit-error-rate performance of the fast-frequency-hopped spread-spectrum multiple-access (FFH/SSMA) and direct-sequence code-division multiple access (DS/CDMA) systems in a Rician fading channel. Each system has a same data rate, bandwidth and transmits over a Rician fading channel. The results illustrate tradoffs in performance between the FFH/SSMA and DS/CDMA systems as a function of the parameters such as average signal to noise ratio and processing gain. The performance of the FFH/SSMA system is shown to be less sensitive to the change of fading environments, while the change of processing gain and average signal to noise ratio gives considerable affect to the FFH/SSMA system compared with the DS/CDMA system. Without respect to the change of system parameters, for most of Rician fading channels (except non-fading channel), FFH/SSMA system gives better performance than DS/CDMA system in BBR < 10$\^$-3/.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.11
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• pp.123-129
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• 2011

In terrestrial wireless optical communication links, atmospheric effects including turbulence, absorption and scattering have significant impact on the system performance. Based on the analysis of transmission in atmospheric channel concerning 830[nm] wavelength diode laser beam, performance of free space optical (FSO) link utilizing Galilean optics as a laser beam transmitting and receving optics, PIN photodiode as a detecting device. In this paper we designed optical link equation for received optical power and we analyze the atmospheric effects on the signal to noise ratio (SNR) and bit error rate (BER) of an terrestrial FSO system. We show that the possible communication distance for BER=$10^{-9}$ in proposed adverse atmospheric conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.4170-4188
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• 2014

In this study, we present a denoising algorithm for high-frame-rate videos in an ultra-low illumination environment on the basis of Kalman filtering model and a new motion segmentation scheme. The Kalman filter removes temporal noise from signals by propagating error covariance statistics. Regarded as the process noise for imaging, motion is important in Kalman filtering. We propose a new motion estimation scheme that is suitable for serious noise. This scheme employs the small motion vector characteristic of high-frame-rate videos. Small changing patches are intentionally neglected because distinguishing details from large-scale noise is difficult and unimportant. Finally, a spatial bilateral filter is used to improve denoising capability in the motion area. Experiments are performed on videos with both synthetic and real noises. Results show that the proposed algorithm outperforms other state-of-the-art methods in both peak signal-to-noise ratio objective evaluation and visual quality.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.2
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• pp.120-126
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• 2009

In order to reduce the noise quantity in a conversation under the noisy environment it is necessary for the signal processing system to process adaptively according to the noise quantity in order to enhance the performance. Therefore this paper presents a recognition method for noise quantity by linear predictive coefficient using a three layered neural network, which is trained using three kinds of speech that is degraded by various background noises. The performance of the proposed method for the noise quantity was evaluated based on the recognition rates for various noises. In the experiment, the average values of the recognition results were 98.4% or more for such noise using Aurora2 database.