• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1327-1329
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• 1996

This paper presents an active noise control (ANC) algorithm using orthogonalization property of Walsh transform. Conventional ANC algorithm known as filtered-x LMS(FXL) algorithm has a problem of decreasing convergence speed in FIR adaptive filters operating in colored noise environments. Walsh transform decompose an input signal into a set of N uncorrelated components and reduce eigenvalue spread of autocorrelation matrix of input sequences. Computer simulations show that proposed (FXW) algorithm is superier to FXL in convergence speed.

• Journal of the Korea society of information convergence
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• v.7 no.2
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• pp.7-12
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• 2014

Many filters are made in order to dectect the accurate signal. The performance of the filter is evaluated as to remove the noise effectively. It is necessary to determine the threshold value for the accurate evaluation of the filter effectively. In this study, we investigated the optimization of the threshold value. It was used for the triangular wave signal and the power supply noise. SNR change according to the number of samples was studied. As the number of samples increases, SNR saw also stabilizde.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.6
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• pp.355-360
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• 2018

The product developed in this study is a ceramic catalyst filter for 1 ton heavy-oil boiler that can simultaneously process dust and nitrogen oxides. This has been developed for simultaneous processing of nitrogen oxides and dust at high efficiency of hot exhaust gas (approximately $300^{\circ}C$) generated after burning 1 ton heavy oil boiler. Ceramic catalytic filters for 1 tonne heavy-duty glass display are technologies that remove 90% of dust and 85% or more of nitrogen oxides. This is an improved new technology to integrate exhaust ventilation and desiccation devices into one, thereby reducing the production process and improving the economy. To this end, the performance test of the catalytic filter for heavy oil boilers was carried out, and the durability of the PLC circuit was constructed.

• 전기의세계
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• v.30 no.12
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• pp.822-831
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• 1981

Many different schemes of the adaptive observer and controller have been developed for both continuous and discrete systems. In this paper we have presented a new scheme of the reduced order adaptive observer for the single input discrete linear time invariant plant. The output equation of the plant, is transformed into the bilinear form in terms of system parameters and the states of the state variable filters. Using the plant output equation the discrete implicit adaptive observer based on the similar philosophy to Nuyan and Carroll is derived and the parameter adaptation algorithm is derived based on the exponentially weighted least square method. The adaptive model following control system is also constructed according to the proposed observer scheme. The proposed observer and controller are rather than simple structure and have a fast adaptive algorithm, so it may be expected that the scheme is suitable to the practical application of control system design. The effectiveness of the algorithm and structure is illustrated by the computer simulation of a third order system. The simulation results show that the convergence speed is proportinal to the increasing of weighting factor alpha, and that the full order and reduced order observer have similar convergence characteristics.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.3
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• pp.184-193
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• 2014

Machine vision systems is applied for various industries such as optimize your spending, automate your production and maximize your efficiency. This research is effective for most optimal light condition of machine vision that technology was applied bald outside human visual acuity. Image processing converts a target image captured by a CCD camera into a digital signal and then performs various arithmetic operations on the signal to extract the characteristics of the target, such as points, lines, circles, area and length. The mathematical concepts of convolution and the kernel matrix are used to apply filters to signals, to perform functions such as extracting edges and reducing unwanted noise. This research analyze and compares matching ratio with reference image and search for optimal lighting condition in accuracy that user wants coming input image according to brightness change of lighting.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.1
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• pp.1-7
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• 2021

In this paper, we presented the experimental basis for the theoretical background and robustness of the Convolutional Neural Network for object recognition based on artificial intelligence. An experimental result was performed to visualize the weighting filters and feature maps for each layer to determine what characteristics CNN is automatically generating. experimental results were presented on the trend of learning error and identification error rate by checking the relevance of the weight filter and feature map for learning error and identification error. The weighting filter and characteristic map are presented as experimental results. The automatically generated characteristic quantities presented the results of error rates for moving and rotating robustness to geometric changes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.1
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• pp.64-71
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• 1997

Digital communication channels are imparied by linear effects such as dispersion, ISI(intersymbol Interference), fading phenomenon etc. But, the practical channel equalization system is required to design for compensating the nonlinear distortion caused by harmonic distortion etc. This paper is a study on the performance of nonlinear channel equalization using RBF(Radial Basis Funclion) network, which has the equivalent structure to the optimal Basian filter. Expecially, the variance of RBF network is modifiedby nonlinear polynomial filters to compare the convergence characteristic of nonlinear channel equalization. Experimental results show that the modified RBF network achieves the faster convergence property than conventional RBF network. Moreover, the RBF network ofhigher order variance modified represents the better performance than that of lower order variance in the bandpass channels and second/third order polynomial channels.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.1997-2004
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• 1994

A model analysis method has been developed in the paper. The method estimates the modal parameters of multiple input-output systems, assesses their quality, and seperates structural modes form computation ones. The modal parameter extraction algorithm is the least squares method with a finite difference model relating input and output time data. The quality of the estimated system model can be assessed in narrow frequency bands by comparing the measured and model predicted responses in time domain with the aid of digital filters. Structural modes can be effectively separated from computational ones using the convergence factor which represents the pole convergence rate. The modal analysis method has been applied to simulated and experimental vibration data to evaluate its utility and limitations.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.2_2
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• pp.319-324
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• 2024

In this paper, the Artificial Intelligence Space(AI-Space) for human-robot interface is presented, which can enable human-computer interfacing, networked camera conferencing, industrial monitoring, service and training applications. We present a method for representing, tracking, and objects(human, robot, chair) following by fusing distributed multiple vision systems in AI-Space. The article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguous conditions. We propose to track the moving objects(human, robot, chair) by generating hypotheses not in the image plane but on the top-view reconstruction of the scene.

• Journal of Institute of Convergence Technology
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• v.1 no.1
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• pp.41-47
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• 2011

With the world-wide demand on the emission minimization, the needs on the diesel aftertreatment devices with high efficiency are also increasing. In order to effectively develop or design a high-performance diesel particulate filter, a clear understanding on the deposition and regeneration mechanism is required. In the present study, a theory on the lumped parameter model for wall-flow type diesel particulate filters is described focusing on the deposition efficiency, pressure drop inside the filter. The fourth order explicit Runge-Kutta method is utilized for the mass flow rate computation. Engine operation modes with controlled and uncontrolled regeneration options are selected. The computational lumped parameter model is validated by comparing the computed results with the measured data.