• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1737-1744
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• 2004

In the compression methods widely used today, the image compression by VQ is the most popular and shows a good data compression ratio. Almost all the methods by VQ use the LBG algorithm that reads the entire image several times and moves code vectors into optimal position in each step. This complexity of algorithm requires considerable amount of time to execute. To overcome this time consuming constraint, we propose an enhanced self-organizing neural network for color images. VQ is an image coding technique that shows high data compression ratio. In this study, we improved the competitive learning method by employing three methods for the generation of codebook. The results demonstrated that compression ratio by the proposed method was improved to a greater degree compared to the SOM in neural networks.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1
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• pp.5-12
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• 1995

In the case where the set of training vectors constitute clusters, the codevectors of the codebook which is used to compression for speech and images in the vector quantization are regarded as the central vectors of the clusters constituted by given training vectors. In this work, we consider the distribution of Euclidean distance obtaining in the process of searching for the minimum distance between vectors, and propose the method searching for the proper number of and the central vectors of clusters. And then, the proposed method shows more than the about 4[dB] SNR than the LBG algorithm and the competitive learning algorithm

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.347-350
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• 2006

In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition is determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section. Truly, emotion recognition technique is not mature. That is, the emotion feature selection, relevant classification method selection, all these problems are disputable. So, we wish this paper to be a reference for the disputes.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.150-154
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• 2006

In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition are determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.26 no.2
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• pp.151-157
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• 2013

In this paper, properties of pattern using LBG (Linde-Buzo-Gray) Algorithm was explored including the exactness of K-means algorithm and process time of EM (Expectation Maximization) algorithm in order to develop analysis algorithm of partial discharge pattern in a cable using acoustic data analysis system. Partial discharge was measured by generating inner fault due to lamination of XLPE which is used for cable insulation material. Discharge pattern was analysed by changing the number of swarm article to 2, 4, and 6 in order to interpret swarm structure and properties.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.885-886
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• 2008

This paper presents a reference template design method for frame-based classification of underwater transient signals. In the proposed method, framebased feature vectors of each reference signal are clustered by using LBG clustering algorithm to reduce the number of feature vectors in each class. Experimental results have shown that drastic reduction of the reference database can be achieved while maintaining the classification performance with LBG clustering algorithm.

• Journal of the Korea Society of Computer and Information
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• v.5 no.3
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• pp.91-98
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• 2000

In this paper we design implement the speaker verification system for verifying personal identification using voice. Filter bank magnitude was used as a feature parameter and code-book was made using LBG a1gorithm. The code book convert feature parameters into code sequence. The difference between reference pattern and input pattern measures using DTW(Dynamic Time Warping). The similarity measured using DTW and threshold value derived from deviation were used to discriminate impostor from client speaker.

• Journal of Ginseng Research
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• v.41 no.4
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• pp.615-619
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• 2017

Background: Black ginseng has a more potent biological activity than non-steamed ginseng. We investigated the effects of long-term intake of dietary black ginseng extract (BG) on antioxidant activity in aged mice. We also compared the effects of BG on cognitive deficits with those of white ginseng extract (WG) and red ginseng extract (RG). Methods: Ten-month-old mice were fed an AIN-93G-based diet containing 10 g/kg (low dose, L) or 30 g/kg (high dose, H) WG powder, RG powder, or BG powder for 24 wk. We measured serum lipids, the activities of antioxidant enzymes, and malondialdehyde levels. Additionally, the protein expression levels of choline acetyltransferase and vesicular acetylcholine transporter, which are presynaptic cholinergic markers in the cortex and hippocampus of the brain, were measured by western blotting. Results: Triglyceride levels were reduced in all the extract-treated mice, except those in the LBG group. High-density lipoprotein cholesterol levels in the HBG group were higher than those in the control group. Total cholesterol levels were reduced in the LBG group. Additionally, glucose levels in the HBG group were significantly reduced by 41.2%. There were lower levels of malondialdehyde in the LBG group than in the control group. Furthermore, glutathione reductase activity increased in the HWG group and the HRG group. The protein expression levels of choline acetyltransferase and vesicular acetylcholine transporter significantly increased in all the ginseng-treated groups. Conclusion: The results suggest that supplementation with the tested ginseng extracts may suppress the cognitive decline associated with aging, via regulation of the cholinergic and antioxidant defense systems.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.4
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• pp.151-158
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• 2014

In this paper, we introduce an inference system using hard scatter partition method and model the nonlinear process. To do this, we use the hard scatter partition method that partition the input space in the scatter form with the value of the membership degree of 0 or 1. The proposed method is implemented by C-Means clustering algorithm. and is used for the initial center values by means of binary split. by applying the LBG algorithm to compensate for shortcomings in the sensitive initial center value. Hard-scatter-partitioned input space forms the rules in the rule-based system modeling. The premise parameters of the rules are determined by membership matrix by means of C-Means clustering algorithm. The consequence part of the rules is expressed in the form of polynomial functions and the coefficient parameters of each rule are determined by the standard least-squares method. The data widely used in nonlinear process is used to model the nonlinear process and evaluate the characteristics of nonlinear process.

• Korean Journal of Food Science and Technology
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• v.39 no.2
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• pp.138-145
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• 2007

The effects of amylopectin and hydrocolloid (locust bean gum and guar gum) content on wheat flour dough and noodle properties were investigated. As the amount of amylopectin increased, the water absorption rate (farinograph), the tension (tension test), the gel stability (freeze-thawing treatment), and the springiness and the cohesiveness (TPA) increased, but the pasting temperature (RVA), the lightness and yellowness (color measurement), and the hardness (TPA) tended to decrease. In sensory evaluations, the scores for cohesiveness, springiness, and acceptability of cooked noodle increased as the proportion of amylopectin increased. The proper combination of amylose/amylopectin ratio and hydrocolloids improved the freeze-thaw stability and the sensory acceptability of wheat flour dough and noodle.