• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.34S no.4
• /
• pp.42-49
• /
• 1997

A conventional adaptive noise canceller (ANC) using LMS algorithm suffers from the misadjustment of adaptive filter weights due to the gradient-estimate noise by input speech signal at steady state. In this paper, an ANC is proposed which uses the combination of VSLMS (variable step size LMS) and SA (sign algorithm) to improve steady state performance and convergence rate. SA algorithm is applied in speech region to prevent the weights from perturbing by output speech of ANC and VSLMS algorithm is applied to improve convergence rate and channel tracking ability in silence region and adaptive transient region. In compute rsimulation, the performance of the proposed VSLMS-SA combination algorithm is much better than LMS algorithm and the algorithm, recently proposed by greenberg, with adaptation step-size parameter determine dby sum method in convergence rate, channel tracking and steady state performance.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.34S no.9
• /
• pp.77-83
• /
• 1997

We present a fast adaptive block matching algorithm using variable search area and subsampling to estimate motion vector more exactly. In the presented method, the block is classified into one of three motion categories: zero motion vector block, medium-motion bolck or high-motion block according to mean absolute difference of the block. By the simulation, the computation amount of the presented methoe comparable to three step search algorithm and new three step search algorithm. In the fast image sequence, the PSNR of our algorithm increased more than TSS and NTSS, because our algorithm estimated motion vector more accurately.

• Journal of applied mathematics & informatics
• /
• v.29 no.3_4
• /
• pp.813-829
• /
• 2011

In this article, we present a numerical scheme for solving singularly perturbed (i.e. highest -order derivative term multiplied by small parameter) Burgers-Huxley equation with appropriate initial and boundary conditions. Most of the traditional methods fail to capture the effect of layer behavior when small parameter tends to zero. The presence of perturbation parameter and nonlinearity in the problem leads to severe difficulties in the solution approximation. To overcome such difficulties the present numerical scheme is constructed. In construction of the numerical scheme, the first step is the dicretization of the time variable using forward difference formula with constant step length. Then, the resulting non linear singularly perturbed semidiscrete problem is linearized using quasi-linearization process. Finally, differential quadrature method is used for space discretization. The error estimate and convergence of the numerical scheme is discussed. A set of numerical experiment is carried out in support of the developed scheme.

• Proceedings of the KIPE Conference
• /
• 2010.07a
• /
• pp.565-567
• /
• 2010

This paper proposes a new Maximum Power Point Tracking (MPPT) control algorithm for PV-Cell (Photo voltaic) based on Incremental Conductance MPPT algorithm. The ICN (Incremental Conductance method) algorithm is widely used due to the high tracking accuracy and adaptability to the rapidly changing isolation condition. In this paper, a modified ICN MPPT algorithm is proposed. This method adjusts automatically the step-size of reference to track the PV-Cell maximum power point, thus it improves the maximum power point tracking speed and accuracy.

• Communications for Statistical Applications and Methods
• /
• v.9 no.1
• /
• pp.155-166
• /
• 2002

Neural networks have been studied as a popular tool for classification and they are very flexible. Also, they are used for many applications of pattern classification and pattern recognition. This paper focuses on Bayesian approach to feed-forward neural networks with single hidden layer of units with logistic activation. In this model, we are interested in deciding the number of nodes of neural network model with p input units, one hidden layer with m hidden nodes and one output unit in Bayesian setup for fixed m. Here, we use the latent variable into the prior of the coefficient regression, and we introduce the 'sequential step' which is based on the idea of the data augmentation by Tanner and Wong(1787). The MCMC method(Gibbs sampler and Metropolish algorithm) can be used to overcome the complicated Bayesian computation. Finally, a proposed method is applied to a simulated data.

• 유체기계공업학회:학술대회논문집
• /
• 1999.12a
• /
• pp.27-32
• /
• 1999

A numerical study based on the three-dimensional thin-layer Navier-Stokes solver is carried out to analyze the flowfield through a single stage transonic compressor. Explicit four-step Runge-Kutta scheme with spatially variable time step and implicit residual smoothing is used. The governing equations are discretized with exploit finite difference method. Mixed-out average method is used at the interface between rotor and stator. And, an artificial dissipation model is used to assure the stability of solution. The results with k-$\omega$ turbulence model were compared to the results with Baldwin-Lomax model, and physical phenomena of transonic compressor are presented. The two turbulence models give the results that show reasonably good agreements with experimental data.

• Proceedings of the KIEE Conference
• /
• summer
• /
• pp.749-751
• /
• 2004

This paper analyzed the characteristics of the claw pole PM step motor by using 3D FEM. In case of analysing this type of motor, 3 dimensional analysis is necessary for an accurate analysis due to the magnetizing component of the z-axis direction. As a main design variable, the magnetization, width and the effects of skewing was selected. The variation of the detent torque and the back EMF depending on the shape of the pole is also shown.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.61 no.1
• /
• pp.75-79
• /
• 2012

Maximum power point tracking(MPPT) techniques are used in photovoltaic systems to maximize the PV array output power by tracking continuously the maximum power point which depends on panels temperature and on irradiance conditions. This paper proposes a variable step size MPPT algorithm which can improve the MPPT speed and accuracy. Depending on insolation and temperature, the MPPT controller gives optimized step size. The effectiveness of the proposed system is verified thorough PSIM simulation and experiments on a 50[W] prototype. The experimental results confirm that the PV power of the improved P&O method is higher than that of the traditional P&O method.

• Proceedings of the KIEE Conference
• /
• 2003.11c
• /
• pp.689-692
• /
• 2003

In this paper, we propose an adaptive beamforming algorithm for array antenna. The proposed beamforming algorithm, based on Block LMS (Block - Least Mean Squares) algorithm, has a variable step size from coefficient update. This method shows some advantages that the convergence speed is fast and the calculation time can reduced using a block LMS algorithm from frequency domain. As the adaptive parameter approaches a stationary state, it could reduce the number of filter coefficient update with the help of various step size. In this paper we compared the efficiency of the proposed algorithm with a standard LMS algorithm which is a representative method of adaptive beamforming.

• Transactions of Materials Processing
• /
• v.28 no.2
• /
• pp.83-88
• /
• 2019

This paper introduces a new concept - on-line FE model, as applied to metal rolling. The new technology allows for completion of process simulation within a tiny fraction of a second without loss of high-level prediction accuracy inherent to FEM. The three steps of an on-line FE model design namely, process metamorphosis, mesh design, and process variable design, are described in detail. The procedure is demonstrated step by step through designing actual on-line models for the prediction of the dog-bone profile in edge rolling. The validity and prediction accuracy of the on-line FE models are analyzed and discussed.