• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.86-89
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• 2016

실내 위치 인식 기술은 Wi-Fi, Bluetooth Low Energy 등 여러 기술을 통해 시도되어 왔으며, 실내 위치 인식 시스템의 상용화가 급증하는 추세이다. 대표적인 실내 측위 시스템인 Wi-Fi 기반 실내 측위는 고출력으로 넓은 범위에 서비스를 제공해주지만, 각 AP 마다 파워 출력이 다르기 때문에 위치 인식 측면에서의 오차가 발생하고, Bluetooth Low Energy 기반 실내 측위는 10m Cell 내에서는 정확한 인식이 가능하지반, 10m 거리 밖 오차는 매우 크다. UWB(Ultra Wide Band)[1][2][3]는 저전력으로, 3.1~10.6GHz의 대역올 이용하여, Wi-Fi의 10배 이상의 속도로 데이터를 전달한다. 이때, 데이터 전달에 사용되는 전파신호는 레이더 신호와 유사한 특징을 가져 거리측정에 사용될 수 있으며, 실내 측위 시 15cm 이내의 정확도를 가진다. 본 논문에서는 UWB의 광대역을 이용한 핑거프린팅과 정밀 측위를 위한 TDoA 기법을 이용한 정밀 실내 측위 알고리즘을 제안한다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.759-763
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• 1996

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• Elastomers and Composites
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• v.39 no.2
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• pp.121-130
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• 2004

A rubber bushing connects the components of the vehicle each other and reduce the vibration transmitted to the chassis frame. A rubber bushing has the nonlinear characteristics for both the amplitude and the frequency and represents the hysteretic responses under the periodic excitation. In this paper, one-axis durability test is performed to describe the mechanical behavior of typical vehicle elastomeric components. The results of the tests are used to develop m empirical bushing model with an artificial neural network. The back propagation algerian is used to obtain the weighting factor of the neural network. A numerical example is carried out to verify the developed bushing model and the vehicle simulation is performed to show the fidelity of proposed model.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.2 s.314
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• pp.11-18
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• 2007

Back propagation algorithm based on a gradient-decent method has been widely used to the training of a neural network. However, this algorithm have some problems such as dropping the minimum value in a local area according to an initial value and setting the number of units in a hidden layer when training the neural network. Accordingly, to solve the above-mentioned problems, this paper proposes a genetic algorithm using the training method of the neural network. Thus, the improved genetic algorithm using a new crossover and mutation method is proposed to discriminate 3 bit parity. Experiments confirm that the proposed system is effective for training speed after demonstrating for generation gap, the number of units in the hidden layer, and the number of individuals.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.367-372
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• 2008

본 연구는 감조하천에서 조위의 영향을 크게 받는 저 평수위의 수위-유량관계곡선식 개발의 한계를 극복하기 위해 조위의 영향을 고려한 다변수 복합 수위-유량관계곡선식을 개발하였다. 곡선식 개발은 수위-수면차-수위차-유량의 관계를 통해 지수형 곡선식을 개발하였다. 여기서 수면차는 조위와 수위와의 차이며, 이때 조석파의 전파시간에 대한 지체시간을 고려하였다. 수위차는 대상 수위관측소의 전 시간과의 수위차이다. 또한 조위에 의해 발생되는 역유량 자료를 이용한 지수형 곡선식을 개발하고자 유량 조정변수를 추가하였다. 개발된 수위-유량관계곡선식을 한강대교에 적용하여 자동유량측정시설에서 측정된 유량자료와 비교 검토한 결과 경향성에서 일치하였으며, (-)유량의 산정도 가능하였다. 분석기간내의 총 유출량 검토 결과 8.3%의 오차를 보여 본 과업에서 제시된 복합 수위-유량관계곡선식의 적정성을 파악할 수 있었다.

• Journal of the Korea Convergence Society
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• v.8 no.7
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• pp.1-6
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• 2017

This paper presents the design of a frequency measurement device using ADC, EP2AGX FPGA and STM32 processor to accurately measure the frequency of a broadband high frequency signal. The ADC device used in this paper has a sampling frequency of 250 MSPS and a processing frequency bandwidth of 100 MHz. Due to its high sampling frequency, it is difficult to process in ordinary computers or processors, so we implemented the frequency measurement algorithm using the Altra EP2AGX FPGA. The measured frequency is sent to the direction detection controller in real time and fused with the phase signal to calculate the incident azimuth angle of the high frequency signal. The designed frequency measurement device is about 0.2 Mhz in frequency measurement error and 30% less than Anaren DFD-x, which is considered to contribute greatly to the design of radio monitoring and direction detection device.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.5
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• pp.558-565
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• 2013

In this paper, modeling and simulation for performance analysis of high resolution SAR system has been carried out in the time, frequency and numeric domain using ADS Ptolemy simulation tool of Agilent corporation. SAR system consists of antenna, controller and transceiver. Error parameters affecting SAR system performances have been defined, modeled and simulated such as phase noise of frequency synthesizer, amplitude and phase characteristic of TWTA, sampling frequency of waveform generator and I/Q imbalance. Finally, the development requirements of SAR system based on the impulse response function have been derived.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.318-327
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• 2009

In this paper, we propose a 3-D geometric localization method for near-field broadband source in shallow water environments. According to the waveguide invariant theory, slope of the interference pattern which is seen in a sensor spectrogram directly proportional to a range of the source. The relative ratio of the range between source and sensors was estimated by matching of two interference patterns in spectrogram. Then this ratio is applied to the Apollonius's circle which shows the locus of a source whose range ratio from two sensors is constant. Two Apollonius's circles from three sensors make the intersection point that means the horizontal range and the azimuth angle of the source. And this intersection point is constant with source depth. Therefore the source depth can be estimated using 3-D hyperboloid equation whose range difference from two sensors is constant. To evaluate a performance of the proposed localization algorithm, simulation is performed using acoustic propagation program and analysis of localization error is demonstrated. From simulation results, error estimate for range and depth is described within 50 m and 15 m respectively.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.16 no.1
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• pp.14-26
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• 2011

Surface currents were observed by high-frequency (HF) radars off the Keum River estuary from December 2008 to February 2009. The dataset of observed surface currents had data gaps due to the interference of electromagnetic waves and the deteriorating weather conditions. To fill the data gaps an optimal interpolation procedure was developed. The characteristics of spatial correlation in the surface currents off the Keum River estuary were investigated and the spatial data gaps were filled using the optimal interpolation. Then, the temporal and spatial distribution of the interpolated surface currents and the patterns of interpolation error were examined. The correlation coefficients between the surface currents in the coastal region were higher than 0.7 because tidal currents dominate the surface circulation. The sample data covariance matrix (C), spatially averaged covariance matrix with localization ($C^G_{sm}$) and covariance matrix fitted by an exponential function ($C_{ft}$) were used to interpolate the original dataset. The optimal interpolation filled the data gaps and suppressed the spurious data with spikes in the time series of surface current speed so that the variance of the interpolated time series was smaller than that of the original data. When the spatial data coverage was larger (smaller) than 70% of the region, the interpolation error produced by $C^G_{sm}$ ($C_{ft}$) was smaller compared with that by C.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.2
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• pp.66-75
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• 2002

This paper presents an adaptive back propagation algorithm that its able to enhancement for the learning efficiency with updating the learning parameter and varies the number of hidden layer node by the generated error, adaptively. This algorithm is expected to escaping from the local minimum and make the best environment for the convergence of the back propagation neural network. On the simulation tested this algorithm on three learning pattern. One was exclusive-OR learning and the another was 3-parity problem and 7${\times}$5 dot alphabetic font learning. In result that the probability of becoming trapped in local minimum was reduce. Furthermore, the neural network enhanced to learning efficient about 17.6%~64.7% for the existed back propagation.