• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.5
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• pp.181-188
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• 2008

E-Science Grid is designed to cope with computation-intensive tasks and to manage a huge volume of science data efficiently. However, certain tasks may involve more than one grid can offer in computation capability or incur a long wait time on other tasks. Resource sharing among Grids can solve this problem with proper processing-integrity check via audit. Due to their computing-intensive nature, the processing time of e-Science tasks tends to be long. This potential long wait before an audit failure encourages earlier audit mechanism during execution in order both to prevent resource waste and to detect any problem fast. In this paper, we propose a Light-weight, Adaptive and Reliable Audit, LARA, of processing Integrity for e-Science applications. With the LARA scheme. researchers can verify their processing earlier and fast.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.115-118
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• 2000

We present a new variable step size LMS algorithm using the correlation between reference input and error signal of adaptive filter. The proposed algorithm updates each weight of filter by different step size at same sample time. We applied this algorithm to adaptive multip]e-notch filter. Simulation results are presented to compare the performance of the proposed algorithm with the usual LMS algorithm and another variable step algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.360-363
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• 1993

Fuzzy Logic Control immitating human decision making process is a novel control strategy based on expert's experience and knowledge and many process designers are developing its applications. But it is difficult to obtain a set of rules from human operator. And there is a limitation on adjusting to environmental changes. In this paper, we proposed adaptive fuzzy algorithm to overcome these difficulties using weights added to the rules. To verify the validity of this control strategy, we have implemented this algorithm for a DC servo motor with PD-type fuzzy controller.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.4
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• pp.220-225
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• 1988

A class of adaptive controllers with integral action is proposed, which may riject the offset due to any load disturbance on the plant. Effective integral action and robust identification against the offset can be achieved via the zero-gain predictor. The system is improved, in this paper, to be of more generalized structure, and the detuning control weight which can cope with nonminimum-phase systems is tuned on-line. Discrete-time versions of the improved system are developed, which may be more flexible for the choice of the design parameters. The resulting control systems may also be shown to be robust to the unmodelled dynamics.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.259-264
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• 2006

It is well known that the uncertainty of the covariance parameters of the process noise (Q) and the observation errors (R) has a significant impact on Kalman filtering performance. Q and R influence the weight that the filter applies between the existing process information and the latest measurements. Errors in any of them may result in the filter being suboptimal or even cause it to diverge. The conventional way of determining Q and R requires good a priori knowledge of the process noises and measurement errors, which normally comes from intensive empirical analysis. Many adaptive methods have been developed to overcome the conventional Kalman filter's limitations. Starting from covariance matching principles, an innovative adaptive process noise scaling algorithm has been proposed in this paper. Without artificial or empirical parameters to be set, the proposed adaptive mechanism drives the filter autonomously to the optimal mode. The proposed algorithm has been tested using road test data, showing significant improvements to filtering performance.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.2
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• pp.46-52
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• 2003

In this paper, the wavelet watermarking algorithm based on adaptive weight MASK processing as a watermark embedded-method for Copyright Protection of Digital contents is Proposed. Because watermark induce as a noise of original image, the watermark size should be limited for preventing quality losses and embedding watermark into images. Therefore, it should be preserve the best condition of the factors, robustness, capacity and visual quality. Tn order to solve this problem, we propose watermarking embedded method by applying adaptive weight MASK to the algorithm and optimize its efficiency. In that result, the watermarked images are improved about external attack. Specifically, correlation coefficient has over 0.8 on both modifications of brightness and contrast. Also, correlation coefficient of wavelet compression of embedded watermark last by over 0.65.

• The Journal of the Acoustical Society of Korea
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• v.21 no.1
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• pp.62-68
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• 2002

It is well known that the MDVR beamforming outperforms the conventional delay-sum beamformer in the sense of noise rejection and bearing resolution. However, the MDVR method requires long observation time to achieve high frequency resolution. The STMV method uses the steered covariance matrix of sensor data, so it has an ability to form an adaptive weight vector from a single time-series snapshot. But it uses the same weight vector across all frequencies. In this paper, we propose an SSMV method. The basic idea of the SSMV method is to decompose a full frequency band into several subbands to acquire a weight vector for each subband, individually. Also the wrap may be divided into several subarrays in order to reduce a computational load and the bandwidth of each subband. Simulations using real sea trial data show that the proposed SSMV method has good performance with short observation time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5A
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• pp.433-440
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• 2007

In this paper, we have proposed WiBro receiver structure employing joint adaptive antenna scheme at the base station (BS) and the mobile station (MS) and evaluated its performance. In WiBro system, the joint use of transmit beamforming at BS and receive beamforming at MS can improve the SINR significantly and increase the capacity compared to the conventional system. Moreover, power allocation level can be decreased because channel variation can be reduced by using the jointly updated weight. However, it needsthe calculation of the antenna weights in every subcarrier for performance improvement. This could imply an enormous computational burden. However, the computational complexity can be reduced significantly by using the same set of the antenna weights for the adjacent subcarriers instead of calculating antenna weights for every subcarrier. We have analyzed the impact of subcarrier grouping for weight calculation on the system performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.561-566
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• 2021

The optimum kernel size for error-distribution estimation with given error samples cannot be used in the weight adjustment of minimum Euclidean distance between error distributions (MED) algorithms. In this paper, a new adaptive kernel estimation method for convergence enhancement of MED algorithms is proposed. The proposed method uses the average rate of change in error power with respect to a small interval of the kernel width for weight adjustment of the MED learning algorithm. The proposed kernel adjustment method is applied to experiments in communication channel compensation, and performance improvement is demonstrated. Unlike the conventional method yielding a very small kernel calculated through optimum estimation of error distribution, the proposed method converges to an appropriate kernel size for weight adjustment of the MED algorithm. The experimental results confirm that the proposed kernel estimation method for MED can be considered a method that can solve the sensitivity problem from choosing an appropriate kernel size for the MED algorithm.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.395-402
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• 2004

In this paper, we proposed a new method of the large capacity steganography using adaptive threshold on bit planes. Applying fixing threshold, if we insert information into all bit planes, all bit planes showed different image quality. Therefore, we first defined the bit plane weight to solve the fixing threshold problem. We then proposed a new adaptive threshold method using the bit plane weight and the average complexity to increase insertion capacity adaptively. In the experiment, we inserted information into the standard images with the same image quality and same insertion capacity, and we analyzed the insertion capacity and image duality. As a result, the proposed method increased the insertion capacity of about 6% and improved the image quality of about 24dB than fixed threshold method.