• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1368-1375
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• 2013

In this paper, we presents a spatially adaptive noise detection and removal algorithm. Under the assumption that an observed image and the additive noise have Gaussian distribution, the noise parameters are estimated with local statistics, and the parameters are used to define the constraints on the noise detection process, where the first order Markov Random Field (MRF) is used. In addition, an adaptive low-pass filter having a variable window sizes defined by the constraints on noise detection is used to control the degree of smoothness of the reconstructed image. Experimental results demonstrate the capability of the proposed algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.499-502
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• 2010

Because of the substantial increase in program complexity and appearance of mega program, the needs to devide the program into small task with multiple partitions, and perform a scheduling based on the priority is required. And also, a program can be developed on specific environment according to the diversify of development environment. for instance, there are some restrictions upon O/S environment such as Embedded or Windows. therefore, the adaptive scheduling technique which perform multiple task partitioning process regardless environment or O/S is suggested. In this study, Adaptive scheduling technique algorithm and its application to be described.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.3
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• pp.765-774
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• 1996

Computer Integrated Manufacturing(CIM) requires models of manufacturing processes to be implemented on the computer. These models are typically used for determining optimal process control parameters or designing adaptive control systems. In spite of the progress made in the mechanistic modeling, however, empirical models derived from experimental data play a maior role in manufacturing process modeling. This paper describes the development of a meural metwork medel for injection molding. This paper describes the development of a nueral network model for injection molding process. The model uses the CAE analysis data based on Taguchi method. The developed model is, then, compared with the traditional polynomial regression model to assess the applicabilit in practice.

• Advances in aircraft and spacecraft science
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• v.7 no.1
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• pp.1-17
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• 2020

In this paper, a new model-based Fault Detection and Diagnosis (FDD) method for an agile supersonic flight vehicle is presented. A nonlinear model, controlled by a classical closed loop controller and proportional navigation guidance in interception scenario, describes the behavior of the vehicle. The proposed FDD method employs the Inertial Navigation System (INS) data and nonlinear dynamic model of the vehicle to inform fins damage to the controller before leading to an undesired performance or mission failure. Broken, burnt, unactuated or not opened control surfaces cause a drastic change in aerodynamic coefficients and consequently in the dynamic model. Therefore, in addition to the changes in the control forces and moments, system dynamics will change too, leading to the failure detection process being encountered with difficulty. To this purpose, an equivalent aerodynamic model is proposed to express the dynamics of the vehicle, and the health of each fin is monitored by the value of a parameter which is estimated using an adaptive robust filter. The proposed method detects and isolates fins damages in a few seconds with good accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2087-2089
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• 2003

The presence of narrowband interference (NBI) in Direct-sequence code division multiple access (DS/CDMA) systems is an inevitable problem when the interference is strong enough. The improvement in the system performance employs by adaptive narrowband interference suppression techniques. Basically there have been two types of method for narrowband interference suppression estimator/subtracter approaches and transform domain approaches. In this paper the focus is on the type of estimator/subtracter approaches. However, the binary direct sequence (DS) signal, that acts as noise in the prediction process is highly non-Gaussian. The case of a Gaussian interferer with known in an autoregressive (AR) signal or a digital signal and also in a sinusoidal signal (Tone) that included in is paper. The proposed NBI suppression is presence in an adaptive IIR notch filter for lattice structure and more powerful by using a variable step-size algorithm. The simulation results show that the proposed algorithm can significantly increase the convergence rate and improved system performance when compare with adaptive least mean square algorithm (LMS).

• Journal of Korea Game Society
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• v.10 no.3
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• pp.47-59
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• 2010

Differing from most of current studies which recognizing game item cash-trade as simple static system, this study approaches game item cash-trade as Complex Adaptive System through historical analysis. The item-trade is a complex phenomenon converging between cyber-economy and real-economy, and production and consumption process of game-item are evolving dynamically over time. The results are following: first, the early item-trade emerges in endogenously rather than results from purposed system designed by singular actor. Second, after the early item-trade, the trade system as a CAS which various voluntary actors(single user, factory, game company, user community, agency, etc.) participates in is self-organizing for trading safety and efficiency. Third, the complex adaptive item-trade system satisfies actor's needs interdependently and accelerate positive feedback powerfully. This study implies that purposeful control disregarding emergent adaptive item-trade system distorts system efficiency and can lead to unintended policy failure.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.189-192
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• 2001

In this paper, we propose a ADALINE controller using fuzzy-backpropagation algorithm to adjust weight. In the proposed ADALINE controller, using fuzzy algorithm for traning neural network, controller make use of ADALINE due to simple and computing efficiency. This controller includes adaptive learning rate to accelerate teaming. It applies to servo-motor as an controlled process. And then it take a simulation for the position control, so the verify the usefulness of the proposed ADALINE controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.607-612
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• 1998

In this paper, a controller using fuzzy-genetic algorithms is proposed for pat-tracking of WMR. A fuzzy controller is implemented so as to adjust appropriate crossover rate and mutation rate. A genetic algorithms is also implemented to have adaptive adjustment of control gain during optimizing process. To check effectiveness of this algorithms, computer simulation is applied.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.785-787
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• 1999

In this paper, recursive least square algorithm is presented to estimate the parameters of step motor under low-speed operation. Parameter estimation is important for compensating the input current by calculating the ratio of the motor torque constant and detent torque constant that causes torque-ripple in low-speed applications. On-line parameter estimation process is a preliminary procedure to apply step motor to adaptive control. Computer simulation shows that the estimated parameters converge in finite time.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.718-721
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• 1988

In this paper, we develop 256*256*8 bit real-time image digitizer with the IBM-PC as a image processor. With this developed system, we process a chest X-ray image, which is a medical image, using the adaptive algorithm. In the future, we consider that the application of this developed system is extended in the various fields.