• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.1062-1065
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• 2002

We have evaluated the ability of a time-delayed artificial neural network (TDANN) to predict muscle forces using only eletromyographic(EMG) signals. To achieve this goal, tendon forces and EMG signals were measured simultaneously in the gastrocnemius muscle of a dog while walking on a motor-driven treadmill. Direct measurements of tendon forces were performed using an implantable force transducer and EMG signals were recorded using surface electrodes. Under dynamic conditions, the relationship between muscle force and EMG signal is nonlinear and time-dependent. Thus, we adopted EMG amplitude estimation with adaptive smoothing window length. This approach improved the prediction ability of muscle force in the TDANN training. The experimental results indicated that dynamic tendon forces from EMG signals could be predicted using the TDANN, in vivo.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.295-298
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• 2002

This paper presents a fast block-matching algorithm to improve the conventional Three-Step Search (TSS) based method. The proposed Comparison Fast Block Matching Algorithm (CFBMA) begins with DAB for adaptive search range to choose searching method, and searches a part of search window that has high possibility of motion vector like other partial search algorithms. The CFBMA also considers the opposite direction to reduce local minimum, which is ignored in almost conventional based partial search algorithms. CFBMA uses the summation half-stop technique to reduce the computational load. Experimental results show that the proposed algorithm achieves the high computational complexity compression effect and very close or better image quality compared with TSS, SES, NTSS based partial search algorithms.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.9
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• pp.429-434
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• 2006

In this paper, detection based - adaptive windowed nonlinear filter(DB-AWNF) is proposed for removing salt-pepper noise in infrared image. This filter is composed of impulse detector and window-size-variable median filters. Impulse detector checks whether current pixel is impulse or not using range function and nonlinear location estimator. If impulse is detected, current pixel is filtered according to four kinds of local masks by use of median filter. If not, current pixel is delivered to output like identity filter. In Qualitative view, the proposed could have removed heavy corrupted noise up to 30% and reserved the details of image. In quantitative view, PSNR was measured. The proposed could have about 12-31[dB] more improved performance than those of median $(3{\times}3)$ filter and 13-29[dB] more improved performance than those of median $(5{\times}5)$ filter.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.70.3-70.3
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• 2015

After a short description of the telescope, we will report on the recent developments in three main areas: - Commissioning of the last of LBT's first generation instruments, now well underway, - Adaptive Optics (AO) and ground-layer AO progress and planned upgrades, - Interferometry first science results. We will also explore the future of the facility as it moves to full operation and strive to be the first of the ELTs in the decade-long window in which GMT, TMT, and E-ELT break ground and start taking shape.

• Proceedings of the IEEK Conference
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• 2000.11a
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• pp.21-24
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• 2000

End-to-end congestion control mechanism have been critical to the robustness and stability of the Internet. Most of today's Internet traffic is TCP, and we expect this to remain so in the future. TCP/IP is the intermediate transport layer candidate for today's applications. TCP uses an adaptive window-based flow control. The congestion avoidance and control algorithms deployed by TCP aims at using the available network bandwidth. This paper compares different congestion control policies, and proposes the new design mechanism for future public networks

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.963-966
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• 1998

In this paper, a fingerprint classification algorithm is presented. Fingerprint types are classified into five categories: arch, tented arch, left loop, right loop and whorl. Singular points (cores and deltas) are detected using Poincare index on the directional image smoothed by adaptive window size. The method is shown to be robust to the variation of fingerprint image qualaity.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.7-10
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• 1998

In implementing real time video on demand(VOD), the increase of user on internet causes a network traffic congestion. In this paper, we programmed a CGI able to login in VOD home for limiting the number of user in solving the problem, and also applied and adaptive multimedia synchronization technique for controlling video and audio data in a network. In addition, a real time multimedia player was designed and implemented in a personal computer operating at Window95/98/NT.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.178-182
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• 1988

In this study, the motion compensating interpolation algorithm is presented. The presented algorithm allows the unblutted reconstruction of omitted frames. It is shown that the Walker & Rao's estimation algorithm using modified displaced frame difference combined with rectangulat adaptive measurement window increases the reliability of the estimation results. The remark ably improved image quality is achieved by change detection and segmentation.

• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1368-1375
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• 2013

In this paper, we presents a spatially adaptive noise detection and removal algorithm. Under the assumption that an observed image and the additive noise have Gaussian distribution, the noise parameters are estimated with local statistics, and the parameters are used to define the constraints on the noise detection process, where the first order Markov Random Field (MRF) is used. In addition, an adaptive low-pass filter having a variable window sizes defined by the constraints on noise detection is used to control the degree of smoothness of the reconstructed image. Experimental results demonstrate the capability of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1234-1238
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• 2005

As the low power GPS signal is susceptible to interference, interference can seriously degrade the performance of GPS receiver. This paper designs a ANIEF(Adaptive Narrowband Interference Excision in Frequency domain) filter that removes narrow band interferences with low signal loss. This filter uses the pre-correlation technique and attempts to filter out the interference in the frequency domain. The interference excision performance of the designed filter is evaluated for various interferences using the ANIEF filter inserted GPS software receiver and the interference generator. Interferences considered in this paper are single-tone CWI(Continuous Wave Interference), multi-tones CWI, pulsed CWI, and swept CWI. The narrowband interference excision filter in frequency domain is very effective against various interferences and the strong interference with a simple structure. However, the signal power loss is unavoidable while transforming. In this paper, the hamming window and overlap technique are adopted to reduce the signal power loss. Finally, the interference excision performance and the reduced signal power loss of the ANIEF filter are shown.