• The Journal of Korean Institute of Communications and Information Sciences
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• v.9 no.2
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• pp.62-69
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• 1984

The performance of direct-sequence spread spectrum(DS-SS) receiver may be enhanced by using the digital whitening filter. In this paper, the hard limited feedback whitening filter that whiten the interference and noise alone is proposed to obtain the additional resistance to narrowband interference. The recursive solution for the calculation of tap weights is presented and the expression for SNR and BER is derived and compared with the conventional digital whitening filter. As the result of computer simulation it is proved that the error performance is improved considerably.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.406-409
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• 2000

We propose the modified neural network which are paralleled to control nonlinear systems. The proposed method is a direct control method to use inverse model of the plant. Nonlinear systems are divided into two parts; linear part and nonlinear part, and it is controlled by RLS method and recursive multi-layer neural network with each other. We simulate to verify the performance of the proposed method and are compared with conventional direct neural network control method. The proposed control method is improved the control performance than the conventional method.

• Journal of information and communication convergence engineering
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• v.10 no.2
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• pp.205-209
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• 2012

To manufacture a real time digital holographic display system capable of being applied to next-generation television, it is important to rapidly generate a digital hologram. In this paper, we analyze digital hologram rendering based on a computer computation scheme. We analyze previous recursive methods to identify regularity between the depth-map image and the digital hologram.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.2
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• pp.99-104
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• 2002

In this paper, we construct a hybrid intelligent controller based on a fusion scheme of GA(Genetic Algorithm) and FCM(Fuzzy C-Means) clustering-based ANFIS(Adaptive Neuro-Fuzzy Inference System). In the structure identification, a set of fuzzy rules are generated for a given criterion by FCM clustering algorithm. In the parameter identification, premise parameters are optimally searched by adaptive GA. On the other hand, consequent parameters are estimated by RLSE(Recursive Least Square Estimate) to reduce the search space. Finally, we applied the proposed method to the truck backer-upper control and obtained a better performance than previous works.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.755-757
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• 1999

The operational properties of BPF(block-pulse functions) are much applied to the analysis of time-varying linear systems. The integral operational matrix of BPF converts the systems in the form of the differential equation into the algebraic problems. But the errors caused by using the integral operational matrix make it difficult that we exactly analyze time-varying linear systems. So, in this paper, to analyze time-varying linear systems we had used the recursive algorithm derived from the new integral operational matrix. And the usefulness of the proposed method is verified by the example.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.441-444
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• 1992

In this paper, for tracking and filtering seaway information which act as a control disturbance the adaptive notch filter which removes disturbance with fast convergence and stability without changing the value of gain parameter $\mu$ when statistical property of input signal varies rapidly is designed by improving conventional RMXMS(Recursive Maximum Mean Square) algorithm. Besides, in consideration of measurement noise of sensors in underwater vehicle, the system which removes the noise and the disturbance is suggested.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.63.6-63
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• 2002

The technique of backstepping have can avoid cancellations of useful nonlinearities. It is widely used in nonlinear adaptive control. But it is difficult to use this technique for uncertain nonlinear systems. Sliding mode control has robustness and application with feedback linearization. This paper shows that the robustness can be used for back stopping technique to solve the uncertainty problem and to improve the scalar design problem using Control Lyapunov function which is the motivation of back stepping technique with recursive design for high-order systems. In the respect of SMC, the result of this paper does not need to satisfy the matching condition.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.115.2-115
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• 2002

A real-time vehicle simulation system is a key element of a driving simulator because accurate prediction of vehicle motion with respect to driver input is required to generate realistic visual, motion, sound and proprioceptive cues. In order to predict vehicle motion caused by various driving actions of the driver on board the simulator, the vehicle model should consist of complete subsystems. On this paper, a tracked vehicle dynamic model with high efficiency and effectiveness is introduced that has been implemented on a training driving simulator. The multi-body vehicle model is based on recursive formulation and has been automatically generated from a symbolic computation package develop...

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.331-336
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• 1989

Under the condition of stable inverse a billinear model predictive control method for SISO and MIMO system with time delay is derived. For processes subject to a bounded disturbance the proposed control method with a classical recursive adaptation algorithm was shown to be stable in the sense of the convergence of parameter estimates and the boundedness of the control error. Several simulation results demonstrate the characteristics of the proposed bilinear model predictive control method.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.1045-1050
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• 1988

The problem of applying the linear integral filter in analysis and parameter estimation of linear continuous systems is discussed. A discrete-time model, which is equivalent to that obtained using the bilinear z transformation, is derived and employed to predict system output. It is shown that the output error can be controlled through the sampling interval. In order to obtain unbiased estimates, an instrumental variable (IV) method is proposed, where the instrumental variables are constituted using adaptive filtering. Some problems on implementation of the recursive IV algorithm are discussed. Both theoretical analysis and simulation study are given to illustrate the proposed methods.