• Journal of information and communication convergence engineering
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• 제6권3호
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• pp.315-319
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• 2008

This paper describes a method for recognizing and measuring the motion of each individual leukocyte in microvessel from a sequence of images. A spatiotemporal image is generated whose spatial axes are parallel and vertical to vessel region contours. In order to enhance and extract only leukocyte traces with a turned velocity range even under noisy background, we use a combination of a filtering process using Gabor filters with sharp orientation selectivity and a subsequent 3D spatiotemporal grouping process. The proposed method is shown to be effective by experiments using image sequences of two kinds of microcirculation, rat mesentery microvessels and human retinal capillaries.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.512-517
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• 1994

The control system of a precise positioning mechanism with resonance and Coulomb friction has been designed using H$_{\infty}$ control theory, and the control performance has been verified by computer simulation and experimental analysis. The DGKF type H$_{\infty}$ control theory with scalar weighting factors was utilized for designing the control system. The followings have been confirmed from the present study: (1) The system with H$_{\infty}$ control presents better convergence and stability than the system with conventional control (PI-notch filter control). (2) The H$_{\infty}$ control system have good robustness properties for a wide range of operating conditions in the presence of external disturbances such as Coulomb friction and changing mechanical resonant frequency.ncy.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집(한일합동학술편); 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.836-841
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• 1987

Many kinds of conditioning monitoring technique have been studied, so this study has investigated the possibility of checking the trend in the fault diagnosis of ball bearing, one of the elements of rotating machine, by applying the cepstral analysis method using the adaptive noise cancelling (ANC) method. And computer simulation is conducted in oder to identify obviously the physical meaning of ANC. The optimal adaptation gain in adaptive filter is estimated, the performance of ANC according to the change of the signal to noise ratio and convergence of LMS algorithm is considered by simulation. It is verified that cepstral analysis using ANC method is more effective than the conventional cepstral analysis method in bearing fault diagnosis.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2521-2525
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• 2005

In this paper, we presented a predictive control technique, which is based on wavelet neural network (WNN), for the control of chaotic systems whose precise mathematical models are not available. The WNN is motivated by both the multilayer feedforward neural network definition and wavelet decomposition. The wavelet theory improves the convergence of neural network. In order to design predictive controller effectively, the WNN is used as the predictor whose parameters are tuned by error between the output of actual plant and the output of WNN. Also the training method for the finding a good WNN model is the Extended Kalman algorithm which updates network parameters to converge to the reference signal during a few iterations. The benefit of EKF training method is that the WNN model can have better accuracy for the unknown plant. Finally, through computer simulations, we confirmed the performance of the proposed control method.

• 대한전자공학회논문지
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• 제25권4호
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• pp.430-436
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• 1988

LSF(Line Spectral Frequency) derived from LPC has known as a very useful transmission parameter of speech signals, for it has a good linear interpolation characteristics and a low spectrum distortion at low bit rates coding. This paper presents that it is possible to extract directly the formant frequencies of speech signals from LSF parameter without application of FFT algorithm by comparing the distribution of LSF parameter with the frequency distribution of analysis filter. This paper suggests the advanced algorithm that results in improving the speed of convergence at analytic solution method. Also, for the flexibility of parameters, the process that transforms from LSF to LPC is presented.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
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• pp.115-120
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• 1997

System identification is the task of inferring a mathematical description of a dynamic system from a series of measurements of the system. There are several motives for establishing mathematical descriptions of dynamic systems. Typical applications encompass simulation, prediction, fault diagnostics, and control system design. The paper demonstrates that neural networks can be used effective for the identification of nonlinear dynamical systems. The content of this paper concerns dynamic neural network models, where not all inputs to and outputs from the networks are measurable. Only one model type is treated, the well-known Innovation State Space model(Kalman Predictor). The identification is based only on input/output measurements, so in fact a non-linear Extended Kalman Filter problem is solved. Even for linear models this is a non-linear problem without any assurance of convergence, and in spite of this fact an attempt is made to apply the principles from linear models, an extend them to non-linear models. Computer simulation results reveal that the identification scheme suggested are practically feasible.

• Journal of information and communication convergence engineering
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• 제8권3호
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• pp.263-266
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• 2010

In this paper, a novel defected ground structure (DGS) pattern with enhanced effective capacitance (varactor diode) and a hole in PCB center is presented. The increase in effective capacitance enables the new DGS pattern to achieve a lower resonance than the DGS pattern for the same etched square dimension. The hole in the center also can make resonator frequency lower with better characteristic. According to the tunable characteristic of varactor diode, the resonant frequencies can be tunable. Simulation results show that a lower resonance is achieved with active device, compared to a common DGS pattern.

• Journal of information and communication convergence engineering
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• 제7권4호
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• pp.535-538
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• 2009

Speckle noise reduction for ultrasound CT image using morphological adaptive median filtering based on edge preservation is presented in this paper. Speckle noise is multiplicative feature and causes ultrasound image to degrade widely from transducer. An input image is classified into edge region and homogeneous region in preprocessing. The speckle is reduced by morphological operation on the 2D gray scale by using convolution and correlation, and edges are preserved. The adaptive median is processed to reduce an impulse noise to preserve edges. As the result, MAM of the proposed method enhances the image to about 10% in comparison with Winner filter by Edge Preservation Index and PSNR, and 10% to only adaptive median filtering.

• Journal of information and communication convergence engineering
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• 제5권4호
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• pp.333-338
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• 2007

In this paper we propose a new structure of the long code MMSE receiver with pilot channel, which maintians excellent symbol detection capability even in the presence of Rayleigh fading. We explain analytically how the stability of the receiver weight vector, which is critical to the system performance, can be achieved by compensating the error signal as well as received signal vector distorted by fading channel. Computer simulation shows while maintaining better performance than the conventional matched filter receiver, the proposed long code MMSE receiver can extend its period up to $16{\times}T_b$ in a fading environment.

• Journal of information and communication convergence engineering
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• 제6권1호
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• pp.10-14
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• 2008

The robot localization problem is a key problem in making truly autonomous robots. In this work we provide thorough discussions of Ultrasonic Positioning System can be applied to the localization problem. First, we look at the use of Kalman filters and basic concept and the equation involved in Kalman filters. Secondly, we create understanding of how the Kalman filters can be implemented in robot localization. We show our discussion and experiments how Kalman filters applied to the localization problem. Lastly, we perform simulations using Usat Wheel Chair robot in our own general Kalman filters robot monitoring software.