• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.87-90
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• 2003

본 논문에서는 정현파를 이용한 spread-spectrum watermarking 에서 비가청성을 높이기 위한 방법과 효율적인 threshold 설정 방법을 제안한다. 제안하는 방법에서는 spread-spectrum 기법을 사용할 때 계산량이 많이 요구되는 심리음향모델 계산을 피하면서도 가청잡음을 줄이기 위한 방법을 제시한다. 또한 outlier 를 이용하여 워터마크 검출에서 적절한 threshold 설정방법을 제안한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.5
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• pp.2291-2297
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• 2012

X-ray fluorescence sprectrum signal include the continuum. XRF analysis the components of material by the amplitude of peaks. XRF remove the noise and background. To remove the noise, we apply the smoothing filter. And background removal methods applied such as SNIP, Morphology, Threshold methods. In this paper, we applied Threshold using DWT. Interval threshold method divide the some blocks in particular levels. We propose the method that is divided the particular level.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.5
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• pp.853-860
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• 2001

This paper presents the new two denoising methods using wavelet. One is new spatially selective noise filtration(NSSNF) using spatial correlation and the other is undecimated discrete wavelet transform (UDWT) threshold-based. NSSNF got the flexible gain special property of SNR adding new parameter at the existing SSNF and UDWT had superior denosing effect than orthogonal wavelet transform(OWT) applied soft-threshold by applied hard-threshold. We selected additive white gaussian noise(AWGN) in this test environment. Also we analyzed and compared ousting denoising method using SNR as standard of judgement of improvemental effect.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.2
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• pp.140-146
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• 2015

We have studied an efficient threshold level for desired target detection in radar system in the paper. A desired target searching detection method detects desired target according to changing for false alarm probability. This time, false alarm probability is close relation to threshold level. Low threshold level can improve detection for desired target, but detect noise signal. Therefor, This method is not good one. In this paper, we propose efficient threshold level method in order to estimation for desired target. Through simulation, we are analysis and performance to compare general method with proposal method. We show that proposed method is more good proof than general method.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.491-494
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• 2001

실제 화자 인증기를 설계함에 있어서 발생하는 가장큰 문제는, 적은 Enrollment data로 화자 모델이 만들어 지므로 화자 인증기의 성능이 시간이 지남에 따라 굉장히 줄어들게 되는 것과, 미리 훈련된 데이터 만으로 Threshold를 설정함에 따라 차후 실제 사용 시에 발생하는 변이를 고려하지 못하여 역시 성능 저하의 문제를 발생시킨다는 것이다. 위의 문제를 해결하기 위해 이 논문은 화자 모델을 구성하는데 있어 MAP 방법을 적용하고, threshold를 Resetting하는 방법을 적용했다. 본 논문에서 제안한 방법으로 HTER값이 23%정도 줄어듦을 보여준다.

• Proceedings of the Korea Contents Association Conference
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• 2003.05a
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• pp.426-429
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• 2003

This paper proposes the threshold value selection for surface classification of 3-dimensional objects. Pre-existing method which uses the H-curvature and K-curvature has limitation in the practical threshold value selection. For this, this paper proposes the threshold value selection by the statistical method. Finally, the effectiveness of this paper demonstrated by experiment.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.57-66
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• 2002

In this paper, we propose a method for the improvement of EZW encoding algorithm. The EZW algorithm encodes wavelet coefficients using 4 symbols such as POS(POsitive), NEG(NEGative), IZ(Isolated Zero), and ZTR(ZeroTreeRoot) which are determined by the significance of wavelet coefficients. In this paper, we applied threshold to wavelet coefficients to improve the EZW algorithm. The coefficients below the threshold are adjusted to zero to generate more ZTR symbols in the encoding process. The overall EZW image compression system is constructed using run-length coding and arithmetic coding. The system shows remarkable results for various images. We finally present experimentation results.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.1049-1068
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• 2014

Autoregressive models are used to analyze an univariate time series data; however, these methods can be inappropriate when a structural break appears in a time series since they assume that a trend is consistent. Threshold autoregressive models (popular regime-switching models) have been proposed to address this problem. Recently, the models have been extended to two regime-switching models with delay parameter. We discuss two regime-switching threshold autoregressive models from a Bayesian point of view. For a Bayesian analysis, we consider a parametric threshold autoregressive model and a nonparametric threshold autoregressive model using Dirichlet process prior. The posterior distributions are derived and the posterior inferences is performed via Markov chain Monte Carlo method and based on two Bayesian threshold autoregressive models. We present a simulation study to compare the performance of the models. We also apply models to gross domestic product data of U.S.A and South Korea.

• The Journal of the Acoustical Society of Korea
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• v.19 no.5
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• pp.20-26
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• 2000

In speaker verification system the HMM(hidden Markov model) parameter updating using small amount of data and the priori threshold decision are crucial factor for dealing with long-term variability in people voices. In the paper we present the speaker model updating technique which can be adaptable to the session-to-intra speaker variability and the priori threshold determining technique. The proposed technique decreases verification error rates which the session-to-session intra-speaker variability can bring by adapting new speech data to speaker model parameter through Baum Welch re-estimation. And in this study the proposed priori threshold determining technique is decided by a hybrid score measurement which combines the world model based technique and the cohen model based technique together. The results show that the proposed technique can lead a better performance and the difference of performance is small between the posteriori threshold decision based approach and the proposed priori threshold decision based approach.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.163-164
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• 2015

In order to decode the bar code image binarization process is indispensable. The traditional binarization method is a global threshold binarization and local threshold binarization. Global threshold binarization method using a single threshold. In some cases there is a blur, or if the brightness is different from the bar code image. Therefore, binary pattern information is not retained. Local threshold method is binaized pattern information is maintained but processing speed is slow than global threshold binarization. The algorithm for solving this problem, there is modified binary algorithm. In this paper, we proposed hardware IP implemented by Vivado of modified binary algorithm.