• The Journal of the Acoustical Society of Korea
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• v.23 no.6
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• pp.446-453
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• 2004

In this paper, a new adaptive perceptual filter using variable threshold to enhance audio signals degraded by additively nonstationary noise is proposed. The adaptive perceptual filter updates variable threshold each time according to the power of signal and the effect of noise variation. So the noisy audio signal is enhanced by the method which controls a residual noise effectively. The proposed algorithm uses the perceptual filter which transforms a time domain signal into frequency domain and calculates an intensity energy and an excitation energy in bark domain. In this method. the stage updated the response of filter is decided by threshold. The proposed algorithm using vairable threshold effectively controls a residual noise using the energy difference of audio signals degraded by the additive nonstationary noise. The proposed method is tested with the noisy audio signals degraded by nonstationary noise at various signal -to-noise ratios (SNR). We carry out NMR and MOS test when the input SNR is 15dB. 20dB. 25dB and 30dB. An approximate improvement of 17.4dB. 15.3dB, 12.8dB. 9.8dB in NMR and enhancement of 2.9, 2.5, 2.3, 1.7 in MOS test is achieved with the input signals. respectively.

• Journal of the Optical Society of Korea
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• v.6 no.3
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• pp.105-107
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• 2002

We propose 'variable decision threshold technique' to decrease the power penalty induced by low-frequency tones. The proposed scheme uses a simple low-speed receiver to change the decision threshold of the optical receiver according to the low-frequency tones. We demonstrate the proposed method at 2.5 Gb/s.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.8
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• pp.1179-1185
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• 2012

This paper presents a new approach for the detection of seismic events using accumulated changes on time-frequency domain and variable threshold. To detect seismic P-wave arrivals with rapidness and accuracy, it is that the changes on the time and the frequency domains are simultaneously used. Their changes are parameters appropriated to reflect characteristics of earthquakes over moderate magnitude(${\geq}$ magnitude 4.0) and microearthquakes. In addition, adaptively controlled threshold values can prevent false P-wave detections due to low SNR. We tested our method on real earthquakes those have various magnitudes. The proposed algorithm gives a good detection performance and it is also comparable to STA/LTA algorithm in computational complexity. Computer simulation results shows that the proposed algorithm is superior to the conventional popular algorithm (STA/LTA) in the seismic P-wave detection.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.65-70
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• 2018

This paper describes a effective information compressor algorithm for the fourth industrial technology. One of the difficult problems for outdoor is to obtain effective updating process of background images. Because input images generally contain the shadows of buildings, trees, moving clouds and other objects, they are changed by lapse of time and variation of illumination. They provide the lowering of performance for surveillance system under outdoor. In this paper, a effective information algorithm for variable environment variable under outdoor is proposed, which apply the Kalman Estimation Modeling and adaptive threshold on pixel level to separate foreground and background images from current input image. In results, the better SNR of about 3dB~5dB and about 10%~25% noise distribution rate in the proposed method. Furthermore, it was showed that the moving objects can be detected on various shadows under outdoor and better result Information.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.1
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• pp.29-36
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• 2020

In this study, a variable step algorithm is proposed on the basis of the perturb and observe method. The proposed algorithm can follow the maximum power point (MPP) quickly when solar irradiance changes rapidly. The proposed technique uses the voltage change characteristic at the MPP when the environment changes because of insolation or temperature. The MPP is tracked through the voltage control using a variable step method. This method determines the sudden change of solar irradiance by setting the threshold value and operates in fast tracking mode to track the MPP rapidly. When the operation point reaches the MPP, the mode switches to the variable step mode to minimize the steady state error. In addition, the output disturbance is decreased through the optimization of the control method design. The performance of the proposed MPPT algorithm is verified through simulation and experiment.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.11-17
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• 2001

We consider the M/G/1 with Bernoulli feedback, where the served customers wait in the feedback queue for rework with probability p. It is important to decide the moment of dispatching in feedback systems because of the dispatching cost for rework. Up to date, researches have analyzed for the instantaneous-dispatching model or the case that dispatching epoch is determined by the state of feedback queue. In this paper we deal with a dispatching model whose dispatching epoch depends on main queue. We adopt supplementary variable method for our model and a numerical example is given for clarity.

• The Journal of the Acoustical Society of Korea
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• v.20 no.7
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• pp.55-62
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• 2001

In this paper, we propose a new adaptative pruning algorithm which effectively reduces the search space during the recognition process. As maximum probabilities between neighbor frames are highly interrelated, an efficient pruning threshold value can be obtained from the maximum probabilities of previous frames. The main idea is to update threshold at the present frame by a combination of previous maximum probability and hypotheses probabilities. As present threshold is obtained in on-going recognition process, the algorithm does not need any pre-experiments to find threshold values even when recognition tasks are changed. In addition, the adaptively selected threshold allows an improvement of recognition speed under different environments. The proposed algorithm has been applied to a Korean Address recognition system. Experimental results show that the proposed algorithm reduces the search space of average 14.4% and 9.14% respectively while preserving the recognition accuracy, compared to the previous method of using fixed pruning threshold values and variable pruning threshold values.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.927-930
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• 2000

Visual features of lip area play an important role in the visual speech information. We are concerned about correct lip area as region of interest (ROI). In this paper, we propose a robust and fast method for locating the mouth corners. Also, we define a region of interest at mouth during speech. A method, which we have used, only uses the horizontal and vertical image operators at mouth area. This searching is performed by fitting the ROI-template to image with illumination control. Most of the lip extraction algorithms are dependent on luminosity of image. We just used the binary image where the variable threshold is applied. The variable threshold varies to illumination condition. In order to control those variations, the gray-tone is converted to binary image by threshold, which is obtained through Multiple Linear Regression Analysis (MLRA) about divided 2D special region. Thus we obtained the region of interest at mouth area, which is the robust extraction about illumination. A region of interest is automatically extracted.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.65-85
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• 2024

The tail probability of a function of a multivariate random variable is not easy to estimate by the crude Monte Carlo simulation. When the occurrence of the function value over a threshold is rare, the accurate estimation of the corresponding probability requires a huge number of samples. When the explicit form of the cumulative distribution function of each component of the variable is known, the inverse transform likelihood ratio method is directly applicable scheme to estimate the tail probability efficiently. The method is a type of the importance sampling and its efficiency depends on the selection of the importance sampling distribution. When the cumulative distribution of the multivariate random variable is represented by a copula and its marginal distributions, we develop an iterative algorithm to find the optimal importance sampling distribution, and show the convergence of the algorithm. The performance of the proposed scheme is compared with the crude Monte Carlo simulation numerically.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1471-1479
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• 2008

In this paper, we propose a technique to improve Out-Of-Vocabulary(OOV) rejection algorithms in variable vocabulary recognition system which is much used in ASR(Automatic Speech Recognition). The rejection system can be classified into two categories by their implementation method, keyword spotting method and utterance verification method. The utterance verification method uses the likelihood ratio of each phoneme Viterbi score relative to anti-phoneme score for deciding OOV. In this paper, we add speaker verification system before utterance verification and calculate an speaker verification probability. The obtained speaker verification probability is applied for determining the proposed variable-confidence threshold. Using the proposed method, we achieve the significant performance improvement; CA(Correctly Accepted for keyword) 94.23%, CR(Correctly Rejected for out-of-vocabulary) 95.11% in office environment, and CA 91.14%, CR 92.74% in noisy environment.