• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06e
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• pp.232-235
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• 1998

In this paper, we present the modified blind adaptive multiuser detector based on Constant Modulus Algorithm(CMA) for the demodulation of code-division multiple-access(CDMA) signals. Convergence issues are treated, and the performance of three algorithms is compared via computer simulations.

• 전자공학회논문지 IE
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• v.43 no.4
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• pp.52-59
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• 2006

Walking robot is able to move in regular or irregular terrain. It can walk that change adaptive algorithms according to the terrain. Existing papers about adaptive gaits of blind robot are based on intelligent foothold selection. However, this paper proposes a algerian that is based on the variations of stroke and period to adapt the irregular terrain. If thus adaptive algorithms is used, robot can maintain periodic gait walking and constant speed using only force sensor even in the irregular terrain without external sophisticated sensor. In this paper Quadruped robot with 2 DOF in each leg, is walk experiment with the wave gait in regular and irregular terrain. So the adaptive algorithm is proved useful through walk experiment.

• The Journal of the Korea institute of electronic communication sciences
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• v.4 no.3
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• pp.224-229
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• 2009

In this paper, an efficient signal interference control technique to improve the convergence speed of Adaptive transversal filter with LMS algorithm is introduced. The convergence characteristics of the proposed algorithm, whose coefficients are multiply adapted in a symbol time period by recycling the received data, are analyzed to prove theoretically the improvement of convergence speed. According as the step-size parameter ${\mu}$ is increased, the rate of convergence of the algorithm is controlled. Increasing the eigenvalue spread has the effect of controlling down the rate of convergence of the adaptive equalizer and also increasing the steady-state value of the average squared error and also demonstrate the superiority of signal interference control to the filter algorithm increasing convergence speed by (B+1) times due to the data-recycling LMS Algorithms.

• Journal of Biosystems Engineering
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• v.14 no.2
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• pp.80-84
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• 1989

In order to improve the combustion efficiency of the agricultural engine, an ignition timing control system was developed and tested. The control system was composed of the CDI ignition circuit, the microcomputer and the interfacing devices. In this study, the simplicity of the control system and the flexibility of the control strategy were emphasized for the precision, the applicability and the economical efficiency. The hardware was consisted in almost the same compositions as those of the automobile engine. The softwares of the control algorithms were developed to three types depending on the combination of the quasi-adaptive control and the open loop control which had the different spark advance equations according to the input variables such as engine speed, exhaust gas temperature and brake torque. The test results were summarized as follows: 1. By using the computer control system, the fuel consumption efficiency could be improved and the fuel consumption could be reduced by 0 to 57% compared to that of the fixed spark advance system. 2. The fuel consumption of the control mode with the quasi-adaptive algorithm was reduced by average 0.8% compared to that of the control mode without quasi-adaptive algorithm. 3. It was found that the control mode with the quasi-adaptive algorithm adopting single input of engine speed had most applicability and economical efficiency among three types of the control algorithms.

• The Journal of the Acoustical Society of Korea
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• v.7 no.2
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• pp.39-50
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• 1988

It is proposed to use a pair of frequency-domain adaptive digital filters to estimate the magnitude squared coherence (MSC) functions of two signals. Such a method requires less computations than the LMS-MSC algorithm in which the least mean square (LMS) algorithm is applied in the time domain to compute the coefficients of a pair of adaptive digital filters. The frequency-domain adaptive digital filtering algorithms considered in this paper include the constrained frequency domain LMS (CFLMS) and the unconstrained frequency domain LMS (UFLMS) algorithms. The performance of the proposed methods are compared with those of the LMS-MSC algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.12-18
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• 2010

This paper proposes an adaptive robust fuzzy control scheme for path tracking of a wheeled mobile robot with uncertainties. The robot dynamics including the actuator dynamics is considered in this work. The presented controller is composed of a fuzzy basis function network (FBFN) to approximate an unknown nonlinear function of the robot complete dynamics, an adaptive robust input to overcome the uncertainties, and a stabilizing control input. Genetic algorithms are employed to optimize the fuzzy rules of FBFN. The stability and the convergence of the tracking errors are guaranteed using the Lyapunov stability theory. When the controller is designed, the different parameters for two actuator models in the dynamic equation are taken into account. The proposed control scheme does not require the accurate parameter values for the actuator parameters as well as the robot parameters. The validity and robustness of the proposed control scheme are demonstrated through computer simulations.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.20-28
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• 2015

In this paper, we propose an effective tracking algorithm with an appearance model based on features extracted from a video frame with posture variation and camera view point adaptation by employing the non-adaptive random projections that preserve the structure of the image feature space of objects. The existing online tracking algorithms update models with features from recent video frames and the numerous issues remain to be addressed despite on the improvement in tracking. The data-dependent adaptive appearance models often encounter the drift problems because the online algorithms does not get the required amount of data for online learning. So, we propose an effective tracking algorithm with an appearance model based on features extracted from a video frame.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.7-12
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• 1993

This paper presents a generalized truncated least, squares adaptive algorithm and a two-stage design method. The proposed algorithm is directly derived from the normal equation of the generalized truncated least squares method (GTLSM). The special case of the GTLSM, the truncated least squares (TLS) adaptive algorithm, has a distinct features which includes the case of minimum steps estimator. This algorithm seemed to be best in the deterministic case. For real applications in the presence of disturbances, the GTLS adaptive algorithm is more effective. The two-stage design method proposed here combines the adaptive control system design with a conventional control design method and each can be treated independently. Using this method, the validity of the presented algorithms are examined by the simulation studies of an indirect adaptive control.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.46-50
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• 2001

Adaptive signal processing is used to acoustic echo canceller. adaptive noise canceller and adaptive algorithm among adaptive algorithms is mainly used because the structure is simple and computa LMS algorithm has trade-off between the converge speed and the steady state error. In this paper, step-size of adaptive algorithm is varied with orthogonality Principles of optimal filter to get fasts though small steady state error. Time varying step-size is determined proportional to the maximum vector of LMS algorithm. As results of simulations, the adaptive algorithm with proposed time-v compared with conventional ones.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.29-34
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• 2001

This paper is devoted to investigating direct adaptive neural control of nonlinear systems with uncertain or unknown dynamic models. In the direct adaptive neural networks control area, theoretical issues of the existing backpropagation-based adaptive neural networks control schemes. The major contribution is proposing the variable index control approach, which is of great significance in the control field, and applying it to derive new stable robust adaptive neural network control schemes. This new schemes possess inherent robustness to system model uncertainty, which is not required to satisfy any matching condition. To demonstrate the feasibility of the proposed leaning algorithms and direct adaptive neural networks control schemes, intensive computer simulations were conducted based on the flexible joint robot systems and functions.