• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.7
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• pp.12-18
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• 1993

We have proposed a soft-decision decoding method for block codes. With careful examinations of the first hard-decision decoded results, The candidate codewords are efficiently searched for. Thus, we can reduce the decoding complexity (the number of hard-decision decodings) and lower the block error probability. Computer simulation results are presented for the (23,12) Golay code. They show that the decoding complexity is considerably reduced and the block error probability is close to that of the maximum likelihood decoder.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.11a
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• pp.167-171
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• 2004

최근 들어 위성영상은 자료 처리 방식에 따라 지구표면이나 또는 지하면에 대한 다양한 정보(물리적인 정보, 화학적인 정보)를 얻을 수 있고 실제 지구를 가상으로 구현하는 데 활용될 수 있기 때문에 여러 산업에서 활용하고 있다. 또한 분류는 영상에 포함된 여러 가지 대상물을 구별하기 위해서 화소와 비교적 성질이 같은 화소 그룹별 특징에 대응되는 레벨을 지정하는 기술이 요구되며, 최소거리 분류법, 평행사변형법, 마하나로비스거리법(Mahanalobis Distance Method), 최대우도법(Maximum Likelihood Method)등 비교하여 분류를 수행

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.543-557
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• 2006

This paper is concerned with the applicability of the chi-square approximation to the six disparity statistics: the Pearson chi-square, the generalized likelihood ratio, the power divergence, the blended weight chi-square, the blended weight Hellinger distance, and the negative exponential disparity statistic. Three dimensional contingency tables of small and moderate sample sizes are generated to be fitted to all possible hierarchical log-linear models: the completely independent model, the conditionally independent model, the partial association models, and the model with one variable independent of the other two. For models with direct solutions of expected cell counts, point estimates and confidence intervals of the 90 and 95 percentage points of six statistics are explored. For model without direct solutions, the empirical significant levels and the empirical powers of six statistics to test the significance of the three factor interaction are computed and compared.

• ETRI Journal
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• v.32 no.5
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• pp.795-800
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• 2010

Embedding a large vocabulary speech recognition system in mobile devices requires a reduced acoustic model obtained by eliminating redundant model parameters. In conventional optimization methods based on the minimum description length (MDL) criterion, a binary Gaussian tree is built at each state of a hidden Markov model by iteratively finding and merging similar mixture components. An optimal subset of the tree nodes is then selected to generate a downsized acoustic model. To obtain a better binary Gaussian tree by improving the process of finding the most similar Gaussian components, this paper proposes a new distance measure that exploits the difference in likelihood values for cases before and after two components are combined. The mixture weight of Gaussian components is also introduced in the component merging step. Experimental results show that the proposed method outperforms MDL-based optimization using either a Kullback-Leibler (KL) divergence or weighted KL divergence measure. The proposed method could also reduce the acoustic model size by 50% with less than a 1.5% increase in error rate compared to a baseline system.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.149-167
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• 2005

The minimum disparity estimators introduced by Lindsay and Basu (1994) are studied empirically. An extensive simulation in this paper provides a location estimate of the small sample and supplies empirical evidence of the estimator performance for the univariate contaminated normal model. Empirical results show that the minimum generalized negative exponential disparity estimator (MGNEDE) obtains high efficiency for small sample sizes and dominates the maximum likelihood estimator (MLE) and the minimum blended weight Hellinger distance estimator (MBWHDE) with respect to efficiency at the contaminated model.

• International journal of advanced smart convergence
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• v.9 no.1
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• pp.98-108
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• 2020

We consider transmit antenna selection combined with power allocation for quadrature spatial modulation (QSM) systems to improve the error rate performance. The Euclidean distance-based joint optimization criterion is presented for transmit antenna selection and power allocation in QSM. It requires an exhaustive search and thus high computational complexity. Thus its reduced-complexity algorithm is proposed with a strategy of decoupling, which is employed to successively find transmit antennas and power allocation factors. First, transmit antennas are selected without considering power allocation. After selecting transmit antennas, power allocation factors are determined. Simulation results demonstrate considerable performance gains with lower complexity for transmit antenna selected QSM systems with power allocation, which can be achieved with limited rate feedback.

• Speech Sciences
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• v.8 no.4
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• pp.59-72
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• 2001

In this paper, we experimented with speaker change detection that uses a statistical method for NOD (News On Demand) service. A specified speaker's change can find out content of each data in speech if analysed because it means change of data contents in news data. Speaker change detection acts as preprocessor that divide input speech by speaker. This is an important preprocessor phase for speaker tracking. We detected speaker change using GLR(generalized likelihood ratio) distance base division and BIC (Bayesian information criterion) base division among matrix method. An experiment verified speaker change point using BIC base division after divide by speaker unit using GLR distance base method first. In the experimental result, FAR (False Alarm Rate) was 63.29 in high noise environment and FAR was 54.28 in low noise environment in MDR (Missed Detection Rate) 15% neighborhood.

• Korean Journal of Remote Sensing
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• v.30 no.2
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• pp.207-218
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• 2014

The information on the land cover along stream corridor is important for stream restoration and maintenance activities. This study aims to review the different classification methods for mapping the status of stream corridors in Seom River using airborne RGB and CIR digital ortho imagery with a ground pixel resolution of 0.2m. The maximum likelihood classification, minimum distance classification, parallelepiped classification, mahalanobis distance classification algorithms were performed with regard to the improvement methods, the skewed data for training classifiers and filtering technique. From these results follows that, in aerial image classification, Maximum likelihood classification gave results the highest classification accuracy and the CIR image showed comparatively high precision.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.4
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• pp.185-194
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• 2013

Abstract- In distant-talking environments, speech recognition performance degrades significantly due to noise and reverberation. Recent work of Michael L. Selzer shows that in microphone array speech recognition, the word error rate can be significantly reduced by adapting the beamformer weights to generate a sequence of features which maximizes the likelihood of the correct hypothesis. In this approach, called Likelihood Maximizing Beamforming algorithm (Limabeam), one of the method to implement this Limabeam is an UnSupervised Limabeam(USL) that can improve recognition performance in any situation of environment. From our investigation for this USL, we could see that because the performance of optimization depends strongly on the transcription output of the first recognition step, the output become unstable and this may lead lower performance. In order to improve recognition performance of USL, some post-filter techniques can be employed to obtain more correct transcription output of the first step. In this work, as a post-filtering technique for first recognition step of USL, we propose to add a Wiener-Filter combined with Feature Weighted Malahanobis Distance to improve recognition performance. We also suggest an alternative way to implement Limabeam algorithm for Hidden Markov Network (HM-Net) speech recognizer for efficient implementation. Speech recognition experiments performed in real distant-talking environment confirm the efficacy of Limabeam algorithm in HM-Net speech recognition system and also confirm the improved performance by the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.105-113
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• 2007

In this paper, we propose the matching pursuit with damping factors, a new sinusoidal model improving the matching pursuit, for the codecs based on sinusoidal model. The proposed model defines damping factors by using a correlativity of parameters between the current and adjacent frame, and estimates sinusoidal parameters more accurately in analysis frame by using the matching pursuit according to damping factor, and synthesizes the final signal. Then it is possible to model efficiently without interpolation schemes. The proposed sinusoidal model shows a better speech quality without an additional delay than the conventional sinusoidal model with interpolation methods. Through the SNR(signal to noise ratio), the MOS(Mean Opinion Score), LR(Itakura-Saito likelihood ratio), and CD(cepstral distance), we compare the performance of our model with that of matching pursuit using interpolation methods.