• Honam Mathematical Journal
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• v.44 no.4
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• pp.628-635
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• 2022

For another study of soft context and soft concept closely related to formal context and formal concept, in this paper, we propose the notions of conditional concepts, decision concepts and soft decision context based on soft contexts. Subsequently, the notions of consistent soft decision context and consistent set are introduced, and some properties for consistent set of soft decision contexts are investigated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6C
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• pp.588-592
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• 2009

In this paper, we propose a novel method to improve the performance of the global soft decision which is based on the second-order conditional maximum a posteriori (CMAP). Conventional global soft decision scheme has an disadvantage in that the speech absence probability adjusted by a fixed-parameter was sensitive to the various noise environments. In proposed approach using the second-order CMAP, speech absence probability value is more flexible which exploit not only the current observation but also the speech activity decisions in the previous two frames. Experimental results show that the proposed improved global soft decision method based on second-order conditional MAP yields better results compared to the conventional global soft decision technique with the performance criteria of the ITU-T P. 862 perceptual evaluation of speech quality (PESQ).

• The Journal of the Acoustical Society of Korea
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• v.32 no.3
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• pp.279-285
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• 2013

In this paper, we propose a novel speech enhancement method to improve the performance of the conventional global soft decision which is based on the spectral gradient method applied to the ratio of a priori speech absence and presence probability value (q). Conventional global soft decision scheme used a fixed value of q in accordance with the hypothesis assumed, but the proposed algorithm is a technique for improving the speech absence probability which is applied adaptively variable value of q according to the speech presence or absence in the previous two frames and the conditions of the spectral gradient value. Experimental results show that the proposed improved global soft decision method based on the spectral gradient method yields better results compared to the conventional global soft decision technique based on the performance criteria of the ITU-T P. 862 PESQ (Perceptual Evaluation of Speech Quality).

• Journal of applied mathematics & informatics
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• v.38 no.3_4
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• pp.335-349
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• 2020

We present inverse soft rough sets by using inverse soft sets and soft rough sets. We study different approaches for inverse soft rough set and examine the relationships between them. We also discuss and explore the basic properties for these approaches. Moreover we develop an algorithm following these concepts and apply it to a decision-making problem to demonstrate the applicability of the proposed methods.

• The Journal of the Acoustical Society of Korea
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• v.27 no.2
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• pp.75-79
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• 2008

In this paper, we propose a novel speech enhancement technique using global soft decision (GSD) based on the probabilistic outputs of support vector machine (SVM). Generally, speech enhancement algorithms applied soft decision gain modification and noise power estimation have bettor performance than those employing hard decision. Especially, global speech absence probability (GSAP), which is known as an effective measure of the speech absence in each frame, has been adopted to SD-based speech enhancement methods. For this reason, we introduce a new GSAP estimated from the probabilistic output of SVM using sigmoid function. The performance of the proposed algorithm is evaluated by the PESQ and MOS test under various noise environments and yields better results compared with the conventional GSD scheme.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3
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• pp.285-289
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• 2009

In this paper, we propose a novel double-talk detection (DTD) technique based on soft decision in the frequency domain. In the proposed method, global near-end speech presence probability (GNSPP) considering the statistical model assumption and voice activity detection (VAD) decision of the near-end and far-end signal are applied to the DTD algorithm in the frequency domain instead of the traditional hard decision scheme using cross-correlation coefficients. The performance of the proposed algorithm is evaluated by the objective test under various environments, and yields better results compared with the conventional scheme.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.118-123
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• 2007

In this paper, we propose an improved global soft decision for speech enhancement in noise environments. From an examination of statistical model-based speech enhancement, it is shown that the global soft decision has a fundamental drawback at the offset region of speech signals. To overcome the drawback, we apply a new speech enhancement method based on a smoothed Global likelihood ratio to the global soft decision. Performances of the proposed method are evaluated by subjective tests under various environments and yield better results compared with the reported speech enhancement method.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.8 s.350
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• pp.69-76
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• 2006

In this paper, we propose blind adaptation strategies for decision feedback equalizer (DFE) optimizing the operation mode between acquisitionand tracking modes based on adjustable soft decision devices. The proposed schemes select an optimal soft decision device to generate feedback samples for the DFE at a given noise to signal ratio, and apply corresponding adaptation rules which combine a blind infinite impulse response (IIR) filtering adaptation and the decision-directed least mean squared (DD-LMS) DFE adaptation. These adaptation approaches attempt to achieve not only smooth transition between acquisition and tracking of DFE but also mitigation of error propagation.

• Journal of Korea Multimedia Society
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• v.7 no.1
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• pp.73-79
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• 2004

In this paper, we propose an efficient soft decision decoding algorithm for linear block codes. A conventional soft decision decoder have to invoke a hard decision decoder several times to estimate its soft decision values. However, in this method, we may not have candidate codewords, thus it is very difficult to produce soft decision values. We solve this problem by introducing an efficient algorithm to search candidate codewords. By using this, we can highly reduce the cases we cannot find candidate codewords. We estimate the performance of the proposed algorithm by using the computer simulations. The simulation is performed for binary (63, 36) BCH code in fading channel.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.222-228
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• 2010

In this paper, we propose a new approach to noise estimation incorporating spectral deviation with soft decision scheme to enhance the intelligibility of the degraded speech signal in non-stationary noisy environments. Since the conventional noise estimation technique based on soft decision scheme estimates and updates the noise power spectrum using a fixed smoothing parameter which was assumed in stationary noisy environments, it is difficult to obtain the robust estimates of noise power spectrum in non-stationary noisy environments that spectral characteristics of noise signal such as restaurant constantly change. In this paper, once we first classify the stationary noise and non-stationary noise environments based on the analysis of spectral deviation of noise signal, we adaptively estimate and update the noise power spectrum according to the classified noise types. The performances of the proposed algorithm are evaluated by ITU-T P. 862 perceptual evaluation of speech quality (PESQ) under various ambient noise environments and show better performances compared with the conventional method.