• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.9
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• pp.2456-2469
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• 1996

A digital satellite communication channel has a nonlinearity with memory due to saturation characeristis of the high poer amplifier in the satellite and transmitter/receiver linear filter used in the overall system. In this paper, we propose a complex radial basis function network(CRBFN) based adaptive equalizer for compensation of nonlinearities in digital satellite communication channels. The proposed CRBFN untilizes a complex-valued hybrid learning algorithm of k-means clustering and LMS(least mean sequare) algorithm that is an extension of Moody Darken's algorithm for real-valued data. We evaluate performance of CRBFN in terms of symbol error rates and mean squared errors nder various noise conditions for 4-PSK(phase shift keying) digital modulation schemes and compare with those of comples pth order inverse adaptive Volterra filter. The computer simulation results show that the proposed CRBFN ehibits good equalization, low computational complexity and fast learning capabilities.

• Journal of the Korea Society of Computer and Information
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• v.16 no.5
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• pp.101-107
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• 2011

The optimum weight vector is studied to remove interference and jamming signals in adaptive array antenna system. The optimum weight vector is calculated to apply a minimum variance algorithm and cost function in linearly constrained conditions, and accurately estimates target's signal. Adaptive array antenna system is the system which improves signal to noise ratio(SNR) and decreases interference and jammer power. Adaptive array antenna system delays at tap output of antenna array element. Each tap finally makes the complex signal of one in multiplier complex weight. In order to obtain optimum's weight calculation, optimum weight vector is used in this paper. After simulation, resolution is increased below $3^{\circ}$, and sidelobe is decreased about 10 dB.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.58-63
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• 1998

B.Widrow established fundamental relations between the least-mean-square (LMS) algorithm and the digital Fourier transform［1］. By extending these relations, we proposed the short time spectra analysis system using the LMS algorithm［2]. In that paper, we used the normal LMS algorithm on the thought of dealing with only real analytical signal. This algorithm minimizes the real mean-square by recursively altering the complex weight vector at each sampling instant. But, the short time spectra analysis sometimes deals with the complex signal that is outputted from complex analog filter. So, in order to optimize and develop this methods, furthermore it is necessary to derive an algorithm for the complex analytical signal. In this paper, we first discuss the new adaptive system for the spectra analysis using the complex LMS algorithm and then derive convergence condition, time constant of coefficient adjustment and frequency resolution by extending the discussion. Finally, the effectiveness of the proposed method is experimentally demonstrated by applying it to the measurement of transfer performance on complex analog filter.

• Proceedings of the IEEK Conference
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• 2004.06a
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• pp.265-268
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• 2004

In this paper. we propose an adaptive step-size algorithm for the adaptive interference canceller (AIC) in the space-time trellis coded DS-CDMA system. In the AIC, the performance of the blind LMS algorithms that updates the tap-weight vector of the AIC is heavily dependent on the choice of step-size. To improve the performance of the fixed step-size AIC (FS-AIC), the regular adaptive step-size algorithm is extended in complex domain and applied to the joint AIC and ML decoder scheme. Simulation results show that the joint adaptive step-size AIC (AS-AIC) and ML decoder scheme using the proposed algorithm has boner performance than not only the conventional ML decoder but also the joint FS-AIC and ML decoder scheme without much increase of the decoding delay and complexity.

• Steel and Composite Structures
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• v.46 no.1
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• pp.107-114
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• 2023

A new intelligent adaptive control scheme was proposed that combines observer disturbance-based adaptive control and fuzzy adaptive control for a composite structure with a mass-adjustable damper. The most important advantage is that the control structures do not need to know the uncertainty limits and the interference effect is eliminated. Three adjustable parameters in LMI are used to control the gain of the 2D fuzzy control. Binary performance indices with weighted matrices are constructed to separately evaluate validation and training performance using the revalidation learning function. Determining the appropriate weight matrix balances control and learning efficiency and prevents large gains in control. It is proved that the stability of the control system can be ensured by a linear matrix theory of equality based on Lyapunov's theory. Simulation results show that the multilevel simulation approach combines accuracy with high computational efficiency. The M-TMD system, by slightly reducing critical joint load amplitudes, can significantly improve the overall response of an uncontrolled structure.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.461-465
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• 2009

Normally, a distributed computing environment is flexible in controlling complex embedded systems but their software components are becoming complex as these systems are equipped with several platforms and attached to various electronic devices, sensors, and actuators. These systems requires inter-object communication mechanisms to provide fault tolerant and QoS-enabled middleware service support in a distributed system. Generally, a middleware performs analysis of the parameters to ensure the availability and reliability of data dissemination. This paper focuses in particular to designing an application middleware for the specific scenario to improve the high availability and fault tolerance of data thus improving the QoS (Quality of Service) of a distributed system. The performance of an adaptive and highly reliable middleware can be significant based on the selection of vital parameters of the system.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.289-294
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• 1988

This paper describes tbe design and implementation of the adaptive controller to maintain the glood weld quality in gas metal arc welding process. The weld torch travel speed and the surface temperature are taken, respectively, as an input and an output of the welding control system. Because of the very complex phenomena of the process, the input-output dynamic model was experimentally identified by AIC (Akiake Information Criterion). Based on the model structure, the explicit model reference adaptive controller is simulated in order to regulate the output tempernture to the desired level.

• Journal of Communications and Networks
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• v.15 no.5
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• pp.496-503
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• 2013

In an orthogonal frequency division multiplexing system, conventional interpolation techniques cannot correctly balance performance and overhead when estimating dynamic long-delay channels in single frequency networks (SFNs). In this study, classical filter analysis and design methods are employed to derive a complex interpolator for maximizing the resistible echo delay in a channel estimator on the basis of the correlation between frequency domain interpolating and time domain windowing. The coefficient computation of the complex interpolator requires a key parameter, i.e., channel length, which is obtained in the frequency domain with a tentative estimation scheme having low implementation complexity. The proposed complex adaptive interpolator is verified in a simulated digital video broadcasting for terrestrial/handheld receiver. The simulation results indicate that the designed channel estimator can not only handle SFN echoes with more than $200{\mu}s$ delay but also achieve a bit-error rate performance close to the optimum minimum mean square error method, which significantly outperforms conventional channel estimation methods, while preserving a low implementation cost in a short-delay channel.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.862-865
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• 1989

The authors, in this paper, investigate the degree of tracking (i.e. the weak points of Samson) to this discrete-time adaptive control system. A matter of course, the results of tracking is improved by using g given in 2.2, compared with the results of Samson. But it is a neck point that the calculation on g is very complex. So by giving the value of g suitably, it is shown that the result superior to one of Samson are taken.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1103-1109
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• 2008

Since the flexible joint robots with motor dynamics are represented by the fifth-order nonlinear sγstem, it is difficult and complex to design the controller for electrically driven flexible-joint (EDFJ) robots. In this paper, we propose a simple adaptive control method to solve this problem. It is assumed that the model uncertainties of the robots dynamics, joint flexibility, and motor dynamics are unknown. For the simple control design, the dynamic surface design method is applied, and all uncertainties in the robot and motor dynamics are compensated by using the adaptive function approximation technique. It is proved that all signals in the controlled closed-loop system are uniformly ultimately bounded. Simulation results for three-link EDFJ manipulators are provided to validate the effectiveness of the proposed control system.