• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.320-322
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• 2002

A new simple spatial scheme for base station with adaptive antenna in Code Division Multiplexing Access (CDMA) systems is presented. In the proposed scheme, by applying the new spatial structure lot the receiver, the system can debate the problem of which the number of users exceeds the number of adaptive antenna elements existing in the conventional spatial scheme. An adaptive algorithm based on the Mean Square Error (MSE) criterion is also derived to update the weight matrix of the proposed scheme. The results of the system capacity enhancement can be achieved by using the proposed approach. Numerical simulations are included fer illustration and verification.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.249-254
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• 2002

In this paper, we propose an adaptive Beamforming Algorithm, called MC-LMS, for adaptive antenna applied to an MC-CDMA system. New method for updating the weight vector based on the MSE criterion is derived. Computer simulations show that MC-LMS algorithm is capable of rejecting co-channel interference that affects the MC-CDMA system. Thus, the BER performance of the MC-CDMA system is much higher than that of the MC-CDMA system without using adaptive antenna and that of the DS-CDMA system with adaptive antenna in multi-path Rayleigh fading channel.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.903-905
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• 2003

In this paper, adaptive high-order neural network controller(AHONNC) is adopted to control of an induction servomotor. A algorithm is developed by combining compensation control and high-order neural networks. Moreover, an adaptive bound estimation algorithm was proposed to estimate the bound of approximation error. The weight of the high-order neural network can be online tuned in the sense of the Lyapunov stability theorem; thus, the stability of the closed-loop system can be guaranteed. Simulation results for induction servomotor drive system are shown to confirm the validity of the proposed controller.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1559-1562
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• 2015

최근 3 차원 깊이 정보를 활용하는 분야가 많아짐에 따라, 정확한 깊이 정보를 추출하기 위한 연구가 계속 진행되고 있다. 특히 ASW(Adaptive Support Weight)는 기존의 영역 기반 알고리즘의 정확도를 향상시키기 위한 방법으로 많이 이용되고 있다. 그 중에서 ACT(Adaptive Census Transform)는 폐백 영역이나 경계 영역에서 정확도가 낮다는 단점이 있었다. 본 논문에서는 정확한 깊이 맵 (depth map)을 추출하기 위해, 기존의 ACT를 개선한 스테레오 정합 알고리즘을 제안한다. 이는 잡음에 강하고 재사용성이 높은 MSW(Multiple Sparse Windows)를 기반으로, TAD(Truncated Absolute Difference)와 ACT 두 개의 정합 알고리즘을 동시에 사용하여 폐색 영역과 울체의 경계 영역에서 정확도가 낮은 기존의 방법을 개선한다. Middlebury에서 제공하는 영상을 사용한 시뮬레이션 결과는 제안한 방법이 기존의 방법보다 평균적으로 약 1.9% 낮은 에러율(error rate)을 가짐을 보여준다.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.2
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• pp.112-124
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• 2004

A neural network based adaptive reconfigurable flight controller is presented for a class of discrete-time nonlinear flight systems in the presence of variations of aerodynamic coefficients and control effectiveness decrease caused by control surface damage. The proposed adaptive nonlinear controller is developed making use of the backstepping technique for the angle of attack, sideslip angle, and bank angle command following without two time separation assumption. Feedforward multilayer neural networks are implemented to guarantee reconfigurability for control surface damage as well as robustness to the aerodynamic uncertainties. The main feature of the proposed controller is that the adaptive controller is developed under the assumption that all of the nonlinear functions of the discrete-time flight system are not known accurately, whereas most previous works on flight system applications even in continuous time assume that only the nonlinear functions of fast dynamics are unknown. Neural networks learn through the recursive weight update rules that are derived from the discrete-time version of Lyapunov control theory. The boundness of the error states and neural networks weight estimation errors is also investigated by the discrete-time Lyapunov derivatives analysis. To show the effectiveness of the proposed control law, the approach is i]lustrated by applying to the nonlinear dynamic model of the high performance aircraft.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.38 no.3
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• pp.1-8
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• 2001

In the DS/CDMA mobile communication systems, the parallel interference canceller is used in order to reduce the multiple access interference and the multipath fading. It is needed the accurate interference estimate in the multistage parallel cancellation. In this paper, the adaptive cancellation method and the new tentative decision device arc proposed and the performance is analyzed. The adaptive cancellation method uses the normalized least mean square(NLMS) algorithm to calculate the weight adaptively, and new tentative decision device uses the hyperbolic tangent decision with null zone. Computer simulation shows that the proposed scheme has the improved performance and the number of user is increased 48% compared with the conventional receiver.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.2
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• pp.68-73
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• 2012

This paper is an analysis the performance of CDMA system using array antenna beamforming technique in wireless channels. Adaptive array beamforming antenna technique combine receive signal amplitude with phase in array antenna element, and can be incremental spatial filter function a direction of arrival signal using weight value. Through simulation, in this paper, we were an analysis to compare bit error rate of forward and backward channels using array antenna beamforming technique in order to interference signal decrease of CDMA fading enviroment. The result simulation, we get spatial diversity effect by using array antenna system, and improved the performance to MAI interference decrease.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10A
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• pp.1006-1012
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• 2008

This paper presents a Duvall-structure-based adaptive beamforming method which efficiently cancels coherent and incoherent interferences. The proposed method exploits several correlation vectors to increase the dimension of the weight vector, compared to the existing method which uses a single correlation vector only. The increased dimension of the weight vector leads to an improvement in the signal-to-interference plus noise ratio (SINR) performance. Moreover, the proposed method can suppress more interferences than the existing one. Simulation shows that the former is superior to the latter in terms of the steady-state and transient responses.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4573-4584
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• 2015

The traditional feature extraction algorithms for recognition of communication signals can hardly realize the balance between computational complexity and signals' interclass gathered degrees. They can hardly achieve high recognition rate at low SNR conditions. To solve this problem, a novel feature extraction algorithm based on Holder coefficient was proposed, which has the advantages of low computational complexity and good interclass gathered degree even at low SNR conditions. In this research, the selection methods of parameters and distribution properties of the extracted features regarding Holder coefficient theory were firstly explored, and then interval gray relation algorithm with improved adaptive weight was adopted to verify the effectiveness of the extracted features. Compared with traditional algorithms, the proposed algorithm can more accurately recognize signals at low SNR conditions. Simulation results show that Holder coefficient based features are stable and have good interclass gathered degree, and interval gray relation classifier with adaptive weight can achieve the recognition rate up to 87% even at the SNR of -5dB.