• IEIE Transactions on Smart Processing and Computing
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• v.6 no.4
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• pp.276-280
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• 2017

This paper presents computationally efficient image compression for wireless transmission of high-definition video, to adaptively utilize available channel bandwidth and improve image quality. The method indirectly predicts an unknown available channel bandwidth by monitoring encoder buffer status, and adaptively controls a quantization parameter to fully utilize the bandwidth. Experimental results show that the proposed method is robust to variations in channel bandwidth.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.255-260
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• 1988

A robust adaptive control method for a stable nonminimum phase SISO system with unmodelled dynamics is proposed. The robust parameter estimation method of the system with bounded output noise and unmodelled dynamics is employed and a parallel structure is proposed to improve the robustness of adaptive control system. The local stability of the proposed system is shown. Computer simulations are done in order to compare the performance of the proposed structure with the basic structure on various circumstance.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.10
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• pp.112-119
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• 1997

Zerotreeimage coding is known as a simple and effective image comprssion algorithm. It has the property that the compression is generated in order of improtance. Conventionally, a fixed threshold is applied to the entire wavelet coefficients regardless of frequency and local features of an image. In this paper, we propose a new zerotree coding scheme with adaptive threshold. The adaptive threshold is determined by human visual characteristics. It is shown that the image quality of the proposed method is better than that of the conventional method.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.78-82
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• 1986

In the process control applications of self tuning control, a major concern of the control problem is to handle an offset caused by load disturbances and random steps occuring at random instance of time. Conventionally an integrator is incorperated in the forward path of the controller to eliminate such an offset. But this approach causes a difficulty if the adaptive part of the resultant controller is to be evaluated. In this paper a method of analyzing the adaptive system and improving the offset effect is suggested for a class of referance model method in the self tuning adaptive control system.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.4
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• pp.597-602
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• 1987

In this paper, an adaptive observe based upon the exponentially weighted least-squares method is implemented in the design of a model reference adaptive controller for an unknown time-invariant discrete single-input single-output linear plant. A method of selecting the state variable filter is proposed. In this scheme, all the past data are weithted exponentially with the weighting coefficient.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.12
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• pp.884-893
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• 1988

Adaptive controllers for linear unknown coefficient system, that is corrupted by disturbance, are designed by parameter adaptation model reference adaptive control(MRAC). This design is stemmed from the Lyapunov direct method. To reduce the model following error and to improve the convergence rate of the design, an indirect-suboptimal control law is derived. Proper compensation for the effects of time-varying coefficients and plant disturbance are suggested. In the design procedure no complete identification of unknown coefficients are required.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.420-420
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• 2000

In this paper, we propose an adaptive controller using RBFN(radial basis function network) for robot manipulators The structure of the proposed controller consists of a RBFN and VSC-1 ike control. RBFN is used in order to approximate かon system, and VSC-like control to guarantee robustness On the basis of the Lyapunov stability theorem, we guarantee the stability for the total system. And the learning law of RBFN is established by the Lyapunov method, Finally, we apply the proposed controller to tracking control for a 2 link SCARA type robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.367-367
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• 2000

In this paper, an Adaptive neuro-fuzzy Inference system(ANFIS) using fuzzy min-max network(FMMN) is proposed. Fuzzy min-max network classifier that utilizes fuzzy sets as pattern classes is described. Each fuzzy set is an aggregation of fuzzy set hyperboxes. Here, the proposed method transforms the hyperboxes into gaussian membership functions, where the transformed membership functions are inserted for generating fuzzy rules of ANFIS. Finally, we applied the proposed method to the classification problem of iris data and obtained a better performance than previous works.

• Structural Engineering and Mechanics
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• v.6 no.1
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• pp.115-124
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• 1998

A novel boundary stress resolution method is suggested in this paper, which is based upon the displacements of finite element analysis and of high precision with stress boundary condition strictly satisfied. The method is used to modify the Zienkiewicz-Zhu ($Z^2$) a posteriori error estimator and for the h-version adaptive finite element analysis of crack problems. Successful results are obtained.

• ETRI Journal
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• v.29 no.5
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• pp.694-696
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• 2007

This letter presents an adaptive coefficient scanning method for intra mode coding in H.264. The proposed adaptive scanning uses six alternative scanning orders based on the intra prediction mode. Experimental results show that the proposed method improves the coding efficiency up to 3% compared to conventional scanning methods without additional computations.