• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.35 no.10
• /
• pp.438-444
• /
• 1986

The signal can be modeled as a linear combination of its past values and present and past values of a hypothetical input to system whose output is given signal. Using this model spectral estimation problem can be reduced to estimate the ARMA parameters. This paper presents recursive modified instrumental variable algorithm which can estimate AR and MA parameters. For more accurate estimation, overdetermined modified IV algorithm is also derived. Computer simulations are presented to illustrate the above methods.

• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.427-430
• /
• 1989

For on-line ARMA spectral estimation, the fast transversal filter algorithm of extended least squares method(ETS FTF) is presented. The projection operator, a key tool for geometric approach, is used in the derivation of the algorithm. ELS FTF is a fast time update recursion which is based on the fact that the correlation matrix of ARMA model satisfies the shift invariance property in each block, and thus it takes 10N+31 MADPR.

• The Journal of Engineering Research
• /
• v.3 no.1
• /
• pp.43-46
• /
• 1998

Considerable research in the last three decades has examined the problem of enhancement of speech degraded by additive background noise. We compare traditional methods such as spectral subtraction and Wiener filter, recently proposed psychoacoustic model based methods such as perceptual filter and noise suppression in EVRC in terms of performance and complexity.

• Proceedings of the Korean Geotechical Society Conference
• /
• 1993.06a
• /
• pp.1-14
• /
• 1993

Ground reinforcements is the essential method to prevent the liquefaction of loose sand deposit, However, in the construction of the life lines, it is impossible to treat the whole loose deposit against liquefaction. As an countmeasure for the life lines against the liquefaction, a monitorning system can be considered for an immediate judgement of the liquefaction occurrence during an earthquake. Through shaking table tests on model grounds, pore presure developments were investigated in terms of the surface spectral velocity, which was verified as a tool for the immediate judgement of the liquefaction occurrence.

• Journal of information and communication convergence engineering
• /
• v.8 no.4
• /
• pp.457-460
• /
• 2010

we have analyzed tens of Giga pulse signal generation using sideband injection locking scheme. The numerical model for semiconductor lasers under the strong optical injection is based on the Lang's equation and has been extended in order to take into account the simultaneous injection of the multiple sidebands of the current-modulated laser. The numerical simulation results show that the unselected sidebands will affect the optical and RF-spectral characteristics even though the semiconductor laser is locked to the target sidebands.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2003.10a
• /
• pp.21-28
• /
• 2003

The use of frequency-dependent spectral element matrix (or dynamic stiffness matrix) in structural dynamics may Provide very accurate solutions, while it reduces the number of degrees of freedom to improve the computational efficiency and cost problems. Thus, this paper develops a spectral element model for the coupled thermoelastic beam-plate moving with constant speed under uniform in-plane tension.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.40 no.4
• /
• pp.351-359
• /
• 1991

This paper describes performances of speaker adaptation using a probabilistic spectral mapping matrix in hidden-Markov model(HMM) -based Korean isolated word recognition. Speaker adaptation based on probabilistic spectral mapping uses a well-trained prototype HMM's and is carried out by Viterbi, dynamic time warping, and forward-backward algorithms. Among these algorithms, the best performance is obtained by using the Viterbi approach together with codebook adaptation whose improvement for isolated word recognition accuracy is 42.6-68.8 %. Also, the selection of the initial values of the matrix and the normalization in computing the matrix affects the recognition accuracy.

• Korean Journal of Remote Sensing
• /
• v.30 no.3
• /
• pp.367-373
• /
• 2014

Albedo is one of the critical parameters for understanding global climate change and energy/water balance. In this study, we used red and NIR reflectance from Satellite Pour I'Obervation de la Terre (SPOT)/Vegetation (VGT) S1 product. The product is preprocessed for users that they are atmospherically corrected using Simple Method Atmospheric Correction (SMAC) by Vision on Technology (VITO) for calculating broadband albedo. Roujean's Bi-directional Reflectance Distribution Function (BRDF) model is a semi-empirical method used for BRDF angular integration and inversion. Each kernel of Roujean's model was multi integrated by angle components (i.e., viewing zenith, solar zenith, and relative azimuth angle). Black-sky hemispherical function is integrated by observational angle; whereas, white-sky hemispherical efficient is integrated by incident angle. Estimated spectral albedo of red ($0.61{\sim}0.68{\mu}m$, B2) and near infrared ($0.79{\sim}0.89{\mu}m$, B3) have a good agreement with MODIS albedo products.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.4
• /
• pp.100-106
• /
• 2008

In this paper we apply a discriminative weight training employing power spectral flatness measure (PSFM) to a statistical model-based voice activity detection (VAD) in various noise environments. In our approach, the VAD decision rule is expressed as the geometric mean of optimally weighted likelihood ratio test (LRT) based on a minimum classification error (MCE) method which is different from the previous works in th at different weights are assigned to each frequency bin and noise environments depending on PSFM. According to the experimental results, the proposed approach is found to be effective for the statistical model-based VAD using the LRT.

• Journal of the Institute of Convergence Signal Processing
• /
• v.14 no.1
• /
• pp.1-5
• /
• 2013

The two major problems related to the blood flow in replaced prosthetic heart valve are thrombus formation and hemolysis. Reliability of prosthetic valve is very important because its failure means the death of patient. There are many factors affecting the valvular failures and their representatives are mechanical failure and thrombosis, so early noninvasive detection is essentially required. The purpose of this study is to detect the various thromboses formation by using acoustic signal acquisition and its spectral analysis on the frequency domain. We made the thrombosis models using Polydimethylsiloxane (PDMS) and they are thrombosis model on the disc, around the sewing ring and fibrous tissue growth across the orifice of valve. Using microphone and amplifier, we measured the acoustic signal from the prosthetic valve, which is attached to the pulsatile mock circulation system. A/D converter sampled the acoustic signal and the spectral analysis is the main algorithm for obtaining spectrum. Then the spectrum of normal and 5 different kinds of abnormal valve were obtained. Each spectrum waveform shows a primary and secondary peak. The secondary peak changes according to the thrombus model. To quantitatively distinguish the frequency peak of the normal valve from that of the thrombosed valves, analysis using a neural network was employed. Acoustic measurement has been used as a noninvasive diagnostic tool and is thought to be a good method for detecting possible mechanical failure or thrombus.