• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.469-472
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• 2005

This paper propose about effective speech feature parameter that have robust character in effect of noise in realizing speech recognition system. Established MFCC that is the basic parameter used to ASR(Automatic Speech Recognition) and DCTCs that use DCT in basic parameter. Also, proposed delta-Cepstrum and delta-delta-Cepstrum parameter that reconstruct Cepstrum to have information for variation of speech. And compared recognition performance in using HMM. For dimension reduction of each parameter LDA algorithm apply and compared recognition. Results are presented reduced dimension delta-delta-Cepstrum parameter in using LDA recognition performance that improve more than existent parameter in noise environment of various condition.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.26-35
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• 1997

This paper deals with establishing correspondent points of feature pints and sampling period when we estimate object motion parameters from image information of freely moving objects in space of gravity-free state. Replacing the inertial coordinate system with the camera coordinate system which is equipped within a space robot, it is investigated to be able to analyze a problem of correspond points from image information, and to obtain sequence of angular velocity $\omega$ which determine a motion of object by means of computer simulation. And if a sampling period ${\Delta}t$ is shortened, the relative errors of angular velocity are increased because the relative errors against moving distance of feature points are increased by quantization. In reverse, if a sampling period ${\Delta}t$ is lengthened too much, the relative error are likewise increased because a sampling period is long for angular velocity to be approximated, and we confirmed the precision that grows according to ascending of resolution.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1157-1159
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• 1987

A syntactic and semantic approach is used to make type classification based on feature points(whorl, delta, core) and the shape of flow line around feature points. The image is divided into 30 by 30 subregions which are represented in the average direction and 4-tuple direction component. Next the relaxation process with singularity detection and convergency checking is performed. A set of semantic languages is used to describe the major flow line around the extracted feature points. LR(1) parser and feature transfer function are used to recognize the coded flow patterns. The 72 fingerprint impressions is used to test the proposed approach and the rate of the classification is about 93 percentages.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.99-100
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• 2008

This paper proposes a Gaussian Mixture Model (GMM) - based speech emotion recognition methods using four feature parameters; 1) Fast Fourier Transform(FFT) spectral entropy, 2) delta FFT spectral entropy, 3) Mel-frequency Filter Bank (MFB) spectral entropy, and 4) delta MFB spectral entropy. In addition, we use four emotions in a speech database including anger, sadness, happiness, and neutrality. We perform speech emotion recognition experiments using each pre-defined emotion and gender. The experimental results show that the proposed emotion recognition using FFT spectral-based entropy and MFB spectral-based entropy performs better than existing emotion recognition based on GMM using energy, Zero Crossing Rate (ZCR), Linear Prediction Coefficient (LPC), and pitch parameters. In experimental Results, we attained a maximum recognition rate of 75.1% when we used MFB spectral entropy and delta MFB spectral entropy.

• Proceedings of the KOSOMBE Conference
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• v.1989 no.05
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• pp.45-49
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• 1989

In this paper the feature of background EEG is extracted by LS Prony Method for the analysis of background EEG in the time domain. From the experimential results the alpha band amplitude is the largest among bands and beta band amplitude is larger than that of the delta band and theta band. The sustained time for the alpha band, the beta band, the delta band and the theta band is 2.3461(sec), 1.8980(sec), 0.3120(sec), 0.2930(sec) respectively. Consequently the alpha band and the beta band are maintained in the whole, segment. The delta band, the theta band are existed intermittently in the segment.

• Bulletin of the Korean Chemical Society
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• v.8 no.5
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• pp.398-403
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• 1987

A general theory of polymer adsorption at a semi-permeable oil-water interface of the biphasic solution is presented. The configurational factor of the solution in the presence of the semi-open boundary at the interface is evaluated by the quasicrystalline lattice model. The present theory gives the feature of the bulk concentration equilibria between oil-water subsystems and the surface excesses of ${\Gamma}^{\alpha}$ and ${\Gamma}^\{beta}$ of the polymer segments as a function of the degree of polymerization $\gamma$, the Flory-Huggins parameter in $\beta$-phase $x_{\rho}^{{\beta}_{\rho}}$, the differential adsorption energy parameter in $\beta$-phase $x_{\sigma}^{{\beta}_{\rho}}$, the differential interaction energy parameter ${\Delta}x_{\rho}$ and the bulk concentration of the polymer in ${\beta}-phase ${\varphi}_2^{{\beta(*)}_2}$. From our numerical results, the characteristics of ${\Gamma}^{\alpha}$ are shown to be significantly different from those of ${\Gamma}^{\beta}$ in the case of high polymers, and this would be the most apparent feature of the adsorption behavior of the polymer at a semi-permeable oil-water interface, which is sensitively dependent on ${\Delta}x_{\rho}$ and r.

• Journal of the Korean Magnetic Resonance Society
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• v.21 no.1
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• pp.13-19
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• 2017

Human sterol ${\Delta}8-{\Delta}7$ isomerase, commonly known as emopamil binding protein (EBP), is an essential protein in the cholesterol-synthetic pathway, and mutations of this protein are critically associated with human diseases such as Conradi-Hunermann-Happle or male EBP disorder with neurological defects syndrome. Due to such a clinical importance, EBP has been intensively investigated and some important features have been reported. EBP is a tetra-spanning membrane protein, of which $2^{nd}$, $3^{rd}$, and $4^{th}$ membrane-spanning ${\alpha}$ helices play an important role in its enzymatic function. However, detailed structural feature at atomic resolution has not yet been elucidated, due to characteristic difficulties in dealing with membrane protein. Here, we over-expressed EBP using Escherichia coli and performed detergent screening to find suitable membrane mimetics for structural studies of the protein by NMR. As results, DPC and LMPG could be evaluated as the most favorable detergents to acquire promising NMR spectra for structural study of EBP.

• Journal of Biomedical Engineering Research
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• v.10 no.2
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• pp.131-138
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• 1989

In this paper the feature of background EEG is extracted by LS Prony Method for the analysis of background EEG in the time domain. Autocorrelation leg estimates are not required with the LS Prony method. The Prony method is required any the solution of two serfs of simultaneous linear equation and a polynominal rooting. That the optimal order of this model is the 6-th order is determined by using Akaike' s Information Criterial test. From the experimential results the alpha band amplitude is the largest among alpha band beta band theta band delta band and beta band amplitude is larger than that of the delta band and theta band. The sustained time for the alph a band, the beta band, the delta band and the theta band is 2, 3461 (sec), 0.6490(sec), 0.3120(sec), 0.7046(sec) respectively. Consequenty the alpha band is maintained in the whole subjects, the beta band, the delta band, the theta band are existed intermittently in each subjects.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.8
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• pp.1265-1271
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• 2017

In this paper, the speech parameter fusion method is studied to improve the performance of the conventional emotion recognition system. For this purpose, the combination of the parameters that show the best performance by combining the cepstrum parameters and the various pitch parameters used in the conventional emotion recognition system are selected. Various pitch parameters were generated using numerical and statistical methods using pitch of speech. Performance evaluation was performed on the emotion recognition system using Gaussian mixture model(GMM) to select the pitch parameters that showed the best performance in combination with cepstrum parameters. As a parameter selection method, sequential feature selection method was used. In the experiment to distinguish the four emotions of normal, joy, sadness and angry, fifteen of the total 56 pitch parameters were selected and showed the best recognition performance when fused with cepstrum and delta cepstrum coefficients. This is a 48.9% reduction in the error of emotion recognition system using only pitch parameters.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.10
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• pp.90-99
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• 1992

In this paper, we propose a neural network model for speech recognition. The model consists of feature extraction parts and recognition parts. The interconnection model based on ${\Delta}^2$G operator was used for frequency analysis. Two features, global feature and local feature, were extracted from this model. Recognition parts consist of global grouping stage and local grouping stage. When the input pattern was coded by slope method, the recognition rate of speakers, A and B, was 100%. When the test was performed with the data of 9 speakers, the recognition rate of 91.4% was obtained.