• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.2
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• pp.28-43
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• 1995

This paper concerns with automatic generation of fuzzy rules which can be used for pattern classification. Feature space is recursively subdivided into hyperspheres, and each hypersphere is represented by its centroid and bounding distance. Fuzzy rules are then generated based on the constructed hyperspheres. The resulting fuzzy rules have very simple premise parts, and they can be organized into a hierarchical structure so that classification process can be implemented very rapidly. The experimented results show that the suggested method works very well compared to other methods.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.956-959
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• 2005

The overall goal of this thesis is to develop a new algorithm based on the octree model for geometric and mechanistic milling operation at the same time. Most commercial machining simulators are based on the Z map model, which has several limitations in terms of achieving a high level of precision in five-axis machining simulation. Octree representation being a three-dimensional (3D) decomposition method, an octree-based algorithm is expected to be able to overcome such limitations. With the octree model, storage requirement is reduced. Moreover, recursive subdivision is processed in the boundaries, which reduces useless computations. To achieve a high level of accuracy, fast computation time and less memory consumption, the advanced octree model is suggested. By adopting the supersampling technique of computer graphics, the accuracy can be significantly improved at approximately equal computation time. The proposed algorithm can verify the NC machining process and estimate the material removal volume at the same time.

• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.29-33
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• 2007

In this paper, time-varying parameter of passive telemetry RF sensor system is estimated using RLS(Rescursive $\leq$* Square) algorithm. In order to overcome the problems such as power limits and complication that general RF sensor system including IC chip has, the principle of inductive coupling is applied to model sensor system The model parameter is rearranged for applying RLS algorithm based on mathematical model to the derived model using inductive coupling principle. Time variant parameter of rearranged model is estimated using forgetting factor, and in case measured data is contaminated by noise and modelling error, the performance of RLS algorithm characterized by the convergence of squared error sum is verified by simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.61-64
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using Digital signal processors for robot manipulators. TMS32OC50 is used in implementing real-time adaptive control algorithms to provide advanced performance for robot manipulator. In this paper, an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. Parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm, and controller parameters are determined by the pole-placement method. Performance of self-tuning adaptive controller is illustrated by the simulation and experiment for a SCARA robot.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.923-931
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• 1999

In this paper, a modeling and a robust time-delay control for the reclaimer are investigated. Supplying the same amount of a raw material throughout the reclamation process from the raw yard to a sinter plant is important to keep the quality of the molten steel uniform in blast furnaces. As the actual parameter values of the reclaimer are not available, the boom rotational dynamics are modeled as a second order differential equation with unknown coefficients. The unknown parameters in the nominal model are estimated using a recursive estimation method. Another important factor in the control design of the reclaimer is the large time-delay in output measurement. Assuming a multiplicative uncertainty, that accounts for both the unstructured uncertainty neglected in the modeling and the structured uncertainty contained in the parameter estimation, a robust Smith predictor is designed. A robust stability criterion for the multiplicative uncertainty is also derived. Following the work of Goodwin et al. [4], a quantifying procedure of the multiplicative uncertainty bound, through experiments , is described. Experimental and simulation results are provided.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.165-170
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• 2014

Speech enhancement techniques that remove surrounding noise are stressed to preprocessor of speech recognition. Among the various speech enhancement techniques, Codebook-based Speech Enhancement (CBSE) operates efficiently in non-stationary noise environments. But, CBSE has some problems that inaccurate gains can be estimated if mismatch occur between input noisy signal and trained speech/noise codevectors. In this paper, the Normalized Weighting Factor (NWF) is calculated by long-term noise estimation algorithm based on Signal-to-Noise Ratio, compensated to the conventional inaccurate gains. The proposed CBSE shows better performance than conventional CBSE.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.3
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• pp.442-450
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• 1994

In this paper, the tracking of SFH/MFSK signals by using a paeallel correlator and a bank of BPF which is implemented by DFT recursively is studied. During symbol period, M-ary signal`s spectrum is analyzed by the step of n multiple of sampling period. The bank of BPF output which is stored for hop duration input to the parallel correlator. The time difference of the receiver and the transmitter is corrected by using sampling position and correlation time at which the largest output of correlator is generated. Syncronization signal detection rate and distribution of the largest output of correlator are evaluated by computer simulation in HF channel evironments for the performance analysis of proposed tracking method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.11
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• pp.1423-1428
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• 2011

This paper proposes a learning input shaper with nonlinear actuator dynamics to reduce the residual vibration of flexible systems. The controller is composed of an estimator of the time constant of the nonlinear actuator dynamics, a recursive least squares method, and an iterative updating algorithm. The updating mechanism is modified by introducing a vibration measurement function to cope with the dynamics of nonlinear actuators. The controller is numerically evaluated with respect to parameter convergence and control performance by using a benchmark pendulum system. The feasibility and applicability of the controller are demonstrated by comparing its control performance to that of an existing controller algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2141-2155
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• 2020

In order to meet the requirements of background change, illumination variation, moving shadow interference and high accuracy in object detection of moving camera, and strive for real-time and high efficiency, this paper presents an object detection algorithm based on sparse approximation recursion and sparse coding migration in subspace. First, low-rank sparse decomposition is used to reduce the dimension of the data. Combining with dictionary sparse representation, the computational model is established by the recursive formula of sparse approximation with the video sequences taken as subspace sets. And the moving object is calculated by the background difference method, which effectively reduces the computational complexity and running time. According to the idea of sparse coding migration, the above operations are carried out in the down-sampling space to further reduce the requirements of computational complexity and memory storage, and this will be adapt to multi-scale target objects and overcome the impact of large anomaly areas. Finally, experiments are carried out on VDAO datasets containing 59 sets of videos. The experimental results show that the algorithm can detect moving object effectively in the moving camera with uniform speed, not only in terms of low computational complexity but also in terms of low storage requirements, so that our proposed algorithm is suitable for detection systems with high real-time requirements.

• Structural Monitoring and Maintenance
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• v.3 no.2
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• pp.115-127
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• 2016

It is a challenging problem of assessing the location and extent of structural damages with vibration measurements. In this paper, an improved Extended Kalman filter (EKF) with Tikhonov regularization is proposed to identify structural damages. The state vector of EKF consists of the initial values of modal coordinates and damage parameters of structural elements, therefore the recursive formulas of EKF are simplified and modal truncation technique can be used to reduce the dimension of the state vector. Then Tikhonov regularization is introduced into EKF to restrain the effect of the measurement noise for improving the solution of ill-posed inverse problems. Numerical simulations of a seven-story shear-beam structure and a simply-supported beam show that the proposed method has good robustness and can identify the single or multiple damages accurately with the unknown initial structural state.