• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.696-705
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• 1997

This paper presents an efficient adaptive predistortion technique compensating linear and nonlinear distortions caused by high-power amplifier (HPA) with memory in OFDM systems. The efficient adaptive data predistortion techniques proposed for compensation of HPA with memory in single carrier systems cannot be applied to OFDM systems since the possible input levels for HPA is infinite in OFDM systems. Also, previous adaptive predistortion techniques, based on Volterra series modeling, are not suitable for real-time implementation due to high computational burden and slow convergence rate. In the proposed approach, the memoryless HPA preceded by a linear filter in OFDM systems is modeled by the Wiener system which is then precompensated by the proposed adaptive predistorter with a minimum number of filter taps. An adaptive algorithm for adjusting the proposed adaptive predistorter is derived using the stochastic gradient method. It is demonstrated by computer simulation that the performance of OFDM system suffering from nonlinear distortion can be greatly improved by the proposed efficient adaptive predistorter using a small number of filter taps.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.05a
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• pp.209-214
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• 2005

In this paper, finite element simulation of three-dimensional bulk metal forming processes is performed by an automated adaptive tetrahedral mesh generation scheme. A dynamic data exchange scheme is employed between tetrahedral mesh generator and forging simulator to minimize user intervention. Both number of elements and density distributions are controlled by the octree technique. The presented approach is applied to automatic forging simulation in order to evaluate the efficiency of the developed schemes and the simulation results are compared with $DEFORM^{TM}$.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1365-1373
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• 1999

In many countries including Korea, in order to transmit the more electric power, the higher transmission line voltage is inevitable. So, a rapid reclosing scheme is important for EHV/UHV transmission lines to ensure requirements for high reliability of main lines. A critical aspect of reclosing operation is the extinction of the secondary arc since it must extinguish before successful reclosure can occur. Therefore the accurate simulation techniques of arcing faults are of importance. And successful reclosing switching can be accomplished by adopting a proper method such as HSGS and hybrid scheme to reduce the secondary arc extinction time. First of all, this paper discusses a suggested arc model, which have time dependent resistance for primary arc and piecewise linear approximated arc model for secondary arc. And this simulation technique is applied to Korean 765 kV transmission lines. Also hybrid scheme is simulated and evaluated for the purpose of shortening dead time. For adaptive reclosing scheme, variable dead time control algorithm is suggested. Two kinds of algorithm are tested. One is max tracking algorithm and the other is rms tracking algorithm. According to simulation results, rms tracking has less errors than max tracking. Therefore rms tracking is applied to Korean 765 kV transmission lines with hybrid scheme.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.189-199
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• 2016

Many implantable hearing aids are being developed as alternatives to conventional hearing aids which has inconveniences for use and social stigma that make hearing-impaired people avoid to wear it. Particularly, the fully-implantable middle ear hearing devices (F-IMEHD) are being actively studied for mixed or sensorineural hearing impaired people. In development of F-IMEHD, the most difficult problem is improving the performance of implantable microphone. Recently, Cho et al. have studied the tympanic membrane installed microphone which has better sensitivity and is easier to operate on patient than the microphone implanted under the skin. But, it may cause howling problem due to the feedback signal via oval window and ossicle chain from the transducer on round window in the middle ear cavity, therefore, a feedback canceller is necessary. In this paper, we designed NLMS (normalized least mean square) adaptive feedback canceller for F-IMEHD with tympanic membrane installed microphone and a transducer implemented at round window, and computer simulation was performed to verify its operation. The designed adaptive feedback canceller has a delay filter, a 64 point FIR fixed filter and a 8-tap adaptive FIR filter. Computer simulation of the feedback path is modeled by using the data obtained through human cadaver experiment.

• Journal of Advanced Navigation Technology
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• v.12 no.1
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• pp.22-27
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• 2008

This paper presents adaptive-MMOSPRED method for prediction of resource demands requested by multimedia calls, and shows the performance of the call admission control based on proposed resource prediction method in multimedia wireless networks. The proposed method determines (I-CDP) random variables of the standard normal distribution by using LMS algorithm that minimize errors of prediction in resource demands, while parameters in an existing method are constant all through the prediction time. Our simulation results show that prediction error in adaptive-MMOSPRED method is much smaller than in fixed-MMOSPRED method. Also we can see via simulation the CAC performance based on the proposed method improves the new call blocking performance compared with the existing method under the desired handoff dropping probability.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.479-485
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• 2009

When a part of data is unobserved the marginal likelihood of parameters given the observed data often involves analytically intractable high dimensional integral and hence it is hard to find the maximum likelihood estimate of the parameters. Simulated maximum likelihood(SML) method which estimates the marginal likelihood via Monte Carlo importance sampling and optimize the estimated marginal likelihood has been used in many applications. A key issue in SML is to find a good proposal density from which Monte Carlo samples are generated. The optimal proposal density is the conditional density of the unobserved data given the parameters and the observed data, and attempts have been given to find a good approximation to the optimal proposal density. Algorithms which adaptively improve the proposal density have been widely used due to its simplicity and efficiency. In this paper, we describe a fully adaptive algorithm which has been used by some practitioners but has not been well recognized in statistical literature, and evaluate its estimation performance and robustness via a simulation study. The simulation study shows a great improvement in the order of magnitudes in the mean squared error, compared to non-adaptive or partially adaptive SML methods. Also, it is shown that the fully adaptive SML is robust in a sense that it is insensitive to the starting points in the optimization routine.

• The Journal of the Acoustical Society of Korea
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• v.7 no.4
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• pp.77-85
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• 1988

Many kinds of conditioning monitoring technique have been studied, so this study has inverstigated the possibility of checking the trend in the fault diagnosis of ball bearing, one of the elements of rotating machine, by applying the cepstral analyisis method using the adaptive noise cancelling (ANC) method. And computer simulation is conducted in order to verify the usefulness 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 least mean square 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.

• International journal of advanced smart convergence
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• v.5 no.1
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• pp.34-46
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• 2016

Networked Control System (NCS) has evolved in the past decade through the advances in communication technology. The problems involved in NCS are broadly classified into two categories namely network issues due to network and control performance due to system network. The network problems are related to bandwidth allocation, scheduling and network security, and the control problems deal with stability analysis and delay compensation. Various delays with variable length occur due to sharing a common network medium. Though most delays are very less and mostly neglected, the network induced delay is significant. It occurs when sensors, actuators, and controllers exchange data packet across the communication network. Networked induced delay arises from sensor to controller and controller to actuator. This paper presents an adaptive delay compensation process for efficient control. Though Smith predictor has been commonly used as dead time compensators, it is not adaptive to match with the stochastic behavior of network characteristics. Time delay adaptive compensation gives an effective control to solve dead time, and creates a virtual environment using the plant model and computed delay which is used to compensate the effect of delay. This approach is simulated using TrueTime simulator that is a Matlab Simulink based simulator facilitates co-simulation of controller task execution in real-time kernels, network transmissions and continuous plant dynamics for NCS. The simulation result is analyzed, and it is confirmed that this control provides good performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.172-185
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• 2019

In this paper, we investigate the performance of the diffusion adaptation strategies for parameter estimation in wireless adaptive networks, where the nodes exchange information over noisy and fading wireless channels. This paper shows the differences between the effect of Rayleigh and Rician fading over wireless adaptive networks and proves that the Rician fading is a more practical model in such kinds of networks. Simulation results imply that the effect of Rayleigh fading is more degrading for the estimation process than Rician fading. Also, the simulation results show the performance of adapt then combine (ATC) diffusion algorithm is better than the combine then adapt (CTA) algorithm by merely considering noise in wireless channels. While the performance of CTA prevails ATC over the wireless adaptive network in the presence of noise plus channel fading.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.211-216
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• 2004

In this thesis, we present the Takagi-Sugeno-Kang (TSK) fuzzy model based adaptive controller and adaptive identification for a general class of uncertain nonlinear dynamic systems. We use an estimated model for the unknown plant model and use this model for designing the controller. The hybrid adaptive control combined direct and indirect adaptive control based on TSK fuzzy model is constructed. The direct adaptive law can be showed by ignoring the identification errors and fails to achieve parameter convergence. Thus, we propose an TSK fuzzy model based hybrid adaptive (HA) law combined of the tracking error and the model ins error to adjust the parameters. Using a Lyapunov synthesis approach, the proposed hybrid adaptive control is proved. The hybrid adaptive law (HA) is better than the direct adaptive (DA) method without identifying the model ins error in terms of faster and improved tracking and parameter convergence. In order to show the applicability of the proposed method, it is applied to the inverted pendulum system and the performance is verified by some simulation results.