• The Journal of the Acoustical Society of Korea
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• v.20 no.7
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• pp.47-54
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• 2001

In this paper, we present a variable dimension vector quantization for spectral magnitudes. Espectially, spectral magnitudes of the Harmonic coder, need variable dimension quantizer because those are not fixed dimension. So, this paper present efficient quantization methods. These methods use variable Discrete Cosine Transform(DCT) for spectral magnitude parameters and NSTVQ which is combined odd/even, split and multi-stage structure, proposed quantization methods use Spectral Distortion(SD) for performance measure. Consequently, Multi-Stage Nonsquare Transform Vector Quantization(MSNSTVQ) is the best in performance measure.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.1092-1096
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• 2009

The spectral element modeling is known to provide very accurate structural dynamic characteristics, while reducing the number of degree-of-freedom to resolve the computational and cost problems. Thus, the spectral element model with variational method for an axially moving string subjected to axial tension is developed in the present paper. The high accuracy of the spectral element model is the verified by comparing its solutions with the conventional finite element solutions and exact analytical solutions. The effects of the moving speed and axial tension the vibration characteristics, wave characteristics, and the static and dynamic stabilities of a moving string are investigated.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.08a
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• pp.396-400
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• 1998

문장 독립형 화자인식 시스템에 운율정보 사용을 제안한다. 스펙트럴 특징패턴만을 주로 사용하고 있는 기존의 화자인식 시스템은 채널왜곡이나 기타 잡음환경에서 성능이 크게 저하된다. 그러나 화자의 speaking style을 반영하는 운율정보는 주위환경에 강인한 특성을 갖는다. 적합한 코드북 크기와 피치 컨투어 특징 벡터의 길이를 실험 치로 구하여 자동차 소음과 백색 가우시안 소음이 섞인 음성에 대하여 화자인식 실험을 하였다. 실험 결과 소음 환경에서 운율 정보를 이용한 화자 dsltlr 시스템이 스펙트럴 모델보다 인식율이 높음을 보였다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.1
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• pp.49-58
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• 2000

This paper presents a new color Image coding method which estimates color component Images from luminance image using spectral correlation m wavelet transformed domain More specifically, the wavelet transform is performed to the luminance image(Y), and then, for an efficient quad-tree division to encompass the varying block size, a cost function IS defined using high frequency coefficients generated by wavelet decomposition Next, a scale factor and an offset factor for each the block to minimize the estimation error between luminance image(Y) and R, B Images, are iteratively calculated With respect to the varying block size With associated cost function.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.5
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• pp.795-801
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• 2001

A method of miniaturizing branch line coupler is presented. The method utilizes the microstrip line with overlay(or superstrate). The frequency dependent characteristics, dispersion and characteristic impedance, of this line are obtained by Immitance method in spectral domain and Method of Line. The relevant spectral domain Green's function is given and used to obtain numerical results. The branch line couplers with overlays are designed and fabricated at 2 GHz. The experimental results show that the size of coupler with overlay(${epsilon}_r$=10.2) is 31.4 precent smaller than conventional coupler. This minimized coupler is suitable for Butler Matrix as feeder for mobile communication beam forming antenna.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.165-172
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• 2005

In speech recognition under a noisy environment, it is necessary to construct a system which reduces the noise and enhances the speech. Then it is effective to imitate the human auditory system which has an excellent analytical spectrum mechanism for speech enhancement. Accordingly, this paper proposes an adaptive method using the auditory mechanism which is called lateral inhibition. This method first estimates the noise intensity by neural network, then adaptively adjusts both the coefficients of the lateral inhibition and the adjusting coefficient of amplitude component according to the noise intensity for each input frame. It is confirmed that the proposed method is effective for speech degraded by white noise, colored noise, and road noise based on the spectral distortion measurement.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.69-78
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• 2010

Spectral modeling synthesis (SMS) has been used as a powerful tool for musical sound modeling. This technique considers a sound as a combination of a deterministic plus a stochastic component. The deterministic component is represented by the series of sinusoids that are described by amplitude, frequency, and phase functions and the stochastic component is represented by a series of magnitude spectrum envelopes that functions as a time varying filter excited by white noise. These representations make it possible for a synthesized sound to attain all the perceptual characteristics of the original sound. However, sometimes considerable phase variations occur in the deterministic component by using the conventional SMS for the complex sound such as whale sounds when the partial frequencies in successive frames differ. This is because it utilizes the calculated phase to synthesize deterministic component of the sound. As a result, it does not provide a good spectrum matching between original and synthesized spectrum in higher frequency region. To overcome this problem, we propose a modified SMS that provides good spectrum matching of original and synthesized sound by calculating complex residual spectrum in frequency domain and utilizing original phase information to synthesize the deterministic component of the sound. Analysis and simulation results for synthesizing whale sounds suggest that the proposed method is comparable to the conventional SMS in both time and frequency domain. However, the proposed method outperforms the SMS in better spectrum matching.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.10
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• pp.1125-1131
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• 2014

This work presents a vulnerability assessment procedure for a complex structure using vibration characteristics. The structural behavior of a three-dimensional framed structure subjected to impact forces was predicted using the spectral element method. The Timoshenko beam function was applied to simulate the impact wave propagations induced by a high-velocity projectile at relatively high frequencies. The interactions at the joints were analyzed for both flexural and longitudinal wave propagations. Simulations of the impact energy transfer through the entire structure were performed using the transient displacement and acceleration responses obtained from the frequency analysis. The kill probabilities of the crucial components for an operating system were calculated as a function of the predicted acceleration amplitudes according to the acceptable vibration levels. Following the proposed vulnerability assessment procedure, the vulnerable positions of a three-dimensional combat vehicle with high possibilities of damage generation of components by impact loading were identified from the estimated vibration responses.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.587-599
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• 1995

This paper proposes a method for pattern recognition using spectral analysis and a hybrid genetic-neural-fuzzy networks. The feature vectors using spectral analysis on contour sequences of 2-D images are extracted, and the vectors are not effected by translation, rotation and scale variance. A combined model using the advantages of conventional method is proposed, those are supervised learning BP, global searching genetic algorithm, and unsupervised learning fuzzy c-method. The proposed method is applied to 10 aircraft recognition to confirm the performance of the method. The experimental results show that the proposed method is better accuracy than conventional method using BP or fuzzy c-method, and learning speed is enhanced.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.2
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• pp.162-170
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• 2015

Commute time embedding involves computing the spectral decomposition of the graph Laplacian. It requires the computational burden proportional to $o(n^3)$, not suitable for large scale dataset. Many methods have been proposed to accelerate the computational time, which usually employ the Nystr${\ddot{o}}$m methods to approximate the spectral decomposition of the reduced graph Laplacian. They suffer from the lost of information by dint of sampling process. This paper proposes to reduce the errors by approximating the spectral decomposition of the graph Laplacian using that of the affinity matrix. However, this can not be applied as the data size increases, because it also requires spectral decomposition. Another method called approximate commute time embedding is implemented, which does not require spectral decomposition. The performance of the proposed algorithms is analyzed by computing the commute time on the patch graph.