• Journal of the Optical Society of Korea
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• v.14 no.1
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• pp.22-27
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• 2010

Bit error rate (BER) monitoring is the ultimate goal of performance monitoring in all digital transmission systems as well as optical fiber transmission systems. To achieve this goal, optimization of the decision threshold must also be considered because BER is dependent on the level of decision threshold. In this paper, we analyze a pseudo-error counting scheme and propose an algorithm to achieve both BER monitoring and adaptive decision threshold optimization in optical fiber transmission systems. To verify the effectiveness of the proposed algorithm, we conduct computer simulations in both Gaussian and non-Gaussian distribution cases. According to the simulation results, BER and the optimum decision threshold can be estimated with the errors of < 20% and < 10 mV, respectively, within 0.1-s processing time in > 40-Gb/s transmission systems.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.123-126
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• 2000

In this paper, we propose new watermarking technique using weighting factor decision method in the watermark embedding step and adaptive threshold decision method in the watermark extracting step. In our method, we are determined weighting factor in simple by calculating distance between pixel coefficient and neighborhood pixel coefficients and threshold is adaptively determined by searching the minimized extract error value using histogram of difference value.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.767-783
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• 2013

This paper aims at designing a selective demodulation scheme based on Log-likelihood Ratio threshold (SDLT) instead of the conventional adaptive demodulation (ADM) scheme, by using rateless codes. The major difference is that the Log-likelihood ratio (LLR) threshold is identified as a key factor to control the demodulation rate, while the ADM uses decision region set (DRS) to adjust the bit rate. In the 16-QAM SDLT scheme, we deduce the decision regions over an additive white Gaussian channel, corresponding to the variation of LLR threshold and channel states. We also derived the equations to calculate demodulation rate and bit error rate (BER), which could be proven by simulation results. We present an adaptation strategy for SDLT, and compare it with ADM and adaptive modulation (AM). The simulation results show that our scheme not only significantly outperforms the ADM in terms of BER, but also achieves a performance as good as the AM scheme. Moreover, the proposed scheme can support much more rate patterns over a wide range of channel states.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.391-395
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• 2011

Cognitive radio (CR) technique is a useful tool for improving spectrum utilization by detecting and using the vacant frequency bands while avoiding interference to the primary user. The sensing performance in a CR network can be improved by allowing some CR users to perform cooperative spectrum sensing. In this paper, we propose a new sensing algorithm that utilizes an adaptive energy threshold for cooperative spectrum sensing in which a changeable energy threshold is adopted by the CR users for improving local sensing performance. Through the proposed scheme, the reliability of global decision can be enhanced mainly due to the improvement in local sensing performance.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.11a
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• pp.194-195
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• 2019

In this paper, we propose a frequency location adaptive hard-decision quantization (HDQ) scheme for video coding. A threshold for zero quantized level is adaptively applied to unquantized transform coefficients based on its frequency location in the transform domain. The proposed method achieves an average of 1.13%, 1.57%, and 1.53% of bit-rate reduction in BDBR sense compared to the conventional HDQ scheme respectively in Y, Cb, and Cr under the all intra encoding configuration.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.2
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• pp.187-196
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• 2017

The size of raw data has dramatically increased due to the recent trend of Synthetic Aperture Radar(SAR) development plans for high resolution and high definition image acquisition. The large raw data has an impact on satellite operability due to the limitations of storage and transmission capacity. To improve the SAR operability, the SAR raw data shall be compressed before transmission to the ground station. The Block Adaptive Quantization (BAQ) algorithm is one of the data compression algorithm and has been used for a long time in the spaceborne SAR system. In this paper, an optimization method of BAQ threshold table is introduced using real SAR raw data to prevent the degradation of signal quality caused by data compression. In this manner, a new variation estimation strategy and a new threshold method for block type decision are introduced.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.8
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• pp.17-22
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• 2016

For the self-adaptive equalization of higher-order QAM systems, this paper proposes a new soft decision-directed (SDD) algorithm that opens the eye patterns quickly as well as significantly reducing the error level in the steady-state when it is applied to the initial equalization stage with completely closed eye patterns. The proposed method for M-QAM application minimized the computational complexity of the existing SDD by the symbol estimated based on the two symbols closest to the observation, and greatly simplified the soft decision independently of the QAM order. Furthermore, in the symbol estimating it increased the reliability of the estimates by applying the superior properties of the sigmoid function and avoiding the erroneous estimation of the threshold function. In addition, the initialization performance was improved when an error is generated to update the equalizer, weighting the symbol decision by the threshold function to the error, resulting in an extension of the range of error fluctuations. As a result, the proposed method improves remarkably the computational complexity and the properties of initialization and convergence of the traditional SDD. Through simulations for 64-QAM and 256-QAM under multipath channel conditions with additive noise, the usefulness of the proposed methods was confirmed by comparing the performance of the proposed 2-SDD and two forms of weighted 2-SDD with CMA.

• The Journal of the Korea Contents Association
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• v.4 no.3
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• pp.91-97
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• 2004

Difference image scheme is widely used for motion estimation in moving object tracking system. This scheme contains a binarization step which segments image into background and moving object regions, referring to threshold value. In this paper, we propose a decision algorithm of tracking the threshold value with a differential image. The key idea is analyzing the histogram of the differential image. In addition we evaluate the performance of this method in comparison with conventional scheme. As an experimental result with 60 images, it is found that threshold by the proposed algorithm is very close to optimal threshold selected manually.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1161-1168
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• 2003

In this paper, we propose an improved statistical model-based voice activity detection algorithm and threshold update method. We first improve signal-to-noise ratio by using speech enhancement preprocessing algorithm combined power subtraction method and matched filter, then apply it to LLR test optimum decision rule for improving the performance even in low SNR conditions. And we propose an adaptive threshold update method that was not concerned in any papers. We also perform extensive computer simulations to demonstrate the performance improvement of the proposed VAD algorithm employing the proposed speech enhancement preprocessing algorithm and adaptive threshold update method under various background noise environments. Finally we verify our results by comparing ITU-T G.729 Annex B.