• Journal of electromagnetic engineering and science
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• v.7 no.4
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• pp.183-189
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• 2007

When the M-ary signal experiences the Rayleigh fading, the diversity schemes can reduce the effect of fading since the probability that all the signals components will fade simultaneously is reduced considerably. The symbol error probabilities for various M-ary signals, such as MDPSK(M-ary DPSK) and MPSK(M-ary PSK), are mathematically derived for the Selection Combining 2(SC-2) and Selection Combining 3(SC-3) demodulation system which requires a less complex receiver than maximum ratio combining(MRC). The propagation model used in this paper is the frequency-nonselective slow Rayleigh fading channel corrupted by the additive white gaussian noise(AWGN). The numerical results presented in this paper are expected to provide information for the design of radio system using M-ary modulation method for above mentioned channel environment.

• Journal of electromagnetic engineering and science
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• v.7 no.4
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• pp.201-206
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• 2007

When the M-ary signal experiences the Rayleigh fading, the diversity schemes can reduce the effects of fading since the probability that all the signals components will fade simultaneously are reduced considerably. The symbol error probabilities for various M-ary signals, such as MDPSK, MPSK and MQAM, are mathematically derived for the SC-2(Selection Combining 2) demodulation system, whereby the two signals with the two largest amplitudes are coherently combined among the L branches. On the other hand, maximum ratio combining(MRC) requires the individual signals from each path to be time-aligned, cophased, optimally weighted by their own fading amplitude, and then summed. The propagation model used in this paper is the frequency-nonselective slow Rayleigh fading channel corrupted by the Additive White Gaussian Noise(AWGN). The numerical results presented in this paper are expected to provide information for the design of radio system using M-ary modulation method for above mentioned channel environment.

• Journal of Communications and Networks
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• v.9 no.1
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• pp.1-10
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• 2007

This paper proposes a multimodal generalized Gaussian distribution (MGGD) to effectively model the varying statistical properties of the extrinsic information. A subsidiary maximum likelihood decoding (MLD) algorithm is subsequently developed to dynamically select the most suitable MGGD parameters to be used in the component maximum a posteriori (MAP) decoders at each decoding iteration to derive the more reliable metrics performance enhancement. Simulation results show that, for a wide range of block lengths, the proposed approach can enhance the overall turbo decoding performance for both parallel and serially concatenated codes in additive white Gaussian noise (AWGN), Rician, and Rayleigh fading channels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.7
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• pp.1689-1698
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• 1998

In this paper, we present a new method for estimating the parameters of transient-type signal in additive white Gaussian noise. This method makes use of the truncated singular value decomposition of an extended-order auto-correlation-like matrix based on the linear-prediction model. The method is tested on data consisting of two exponentially dampled sinusoidal signals with the same damping factor and different damping factor. Simulation results are illustrated to demonstrate the better performance of the method applied to the auto-correlation-like matrix than that applied to the data matrix.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.10a
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• pp.63-70
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• 2003

This study investigates the seismic responses of two structures connected by sky-bridges equipped with viscoelastic dampers (VED) in the bridge-building connections. The applicability of the method is verified first by computing RMS responses of two-degrees-of-freedom systems subjected to white noise ground excitation. Then model structures with various number of stories are analyzed using EL CENTRO earthquake excitation to observe the effect of the varying size of VED on reduction of responses. According to the analysis results, there exists a proper size of VED which minimizes the structural responses. It is also observed that the effectiveness of VED increases as the difference of natural frequencies between the two connected structures increases.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.474-478
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• 1998

A new approach for the decision feedback equalizer(DFE) based on the back-propagation neural networks is described. We propose the method of optimal structure for back-propagation neural networks model. In order to construct an the optimal structure, we first prescribe the bounds of learning procedure, and the, we employ the method of incrementing the number of input neuron by utilizing the derivative of the error with respect to an hidden neuron weights. The structure is applied to the problem of adaptive equalization in the presence of inter symbol interference(ISI), additive white Gaussian noise. From the simulation results, it is observed that the performance of the propose neural networks based decision feedback equalizer outperforms the other two in terms of bit-error rate(BER) and attainable MSE level over a signal ratio and channel nonlinearities.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.23-26
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• 2006

Modernized GPS will have three frequencies modulated with three signals, which will be accessible to all users in the near future. This new frequency provides an opportunity to resolve the double differenced (DD) integer ambiguity very fast and with almost no baseline constraints. In order to study the performance of triple frequency system for Ambiguity Resolution (AR) over the medium baseline under different ionospheric levels, the Klobuchar Model was implemented and used in our triple simulation to generate the ionospheric delay. Furthermore, the White-Gaussian noise applying to distance-dependent parameters was added to the DD ionospheric delay. For medium baseline (defined as here 20 to 40kms), success rates of AR has been pretty improved. In this paper, the medium baseline AR strategies that take advantage of carrier phase measurement on the third frequency will be discussed.

• Proceedings of the Korea Water Resources Association Conference
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• 1984.07a
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• pp.89-98
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• 1984

우리나라의 월강우량 기록은 풍부하나 월유출량 기록은 희박하여, 월유출량 시계열의 모형식을 개발하고저 하여 월강우량 기록만으로 하천유량의 정확한 파악을 할 수 있도록 한다. 이 연구는 월강우와 유출량의 시계열에 의한 추계학적 이론에 의거한 복스와 젠킨스의 대체함수(Transfer function model)와 아리마(ARIMA)의 잔차모양을 합한 형이다. 이 선형 추계학적 차분 시계열식 모형은 공본산(coveriance) 을 갖는다는 가정에서 강우량과 유출량의 변화에 따라서 식의 구조가 유도되며 정확하게 잘 적용이 된다. 본 식의 최적모형은 일반식으로 아래와 같이 얻어진다. $ Y$:월유출량, X$:월강우량, C$:유출물, $: 대체변수, a$:백색잡음(white noise), $\theta$(B) 및 (B):MA(Moving average)와 AR(autoregressive)조작, 이번 연구 결과 섬진강 하천의 대체조작(Transfer operator)은 잔차승(Sum of residual) R$0.9로 높은 정도의 수치를 나타내는 것으로 보인다.

• Wind and Structures
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• v.5 no.5
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• pp.423-440
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• 2002

The effects of the nonlinear (quadratic) term in wind pressure have been analyzed in many papers with reference to linear structural models. The present paper addresses the problem of the response of nonlinear structures to stochastic nonlinear wind pressure. Adopting a single-degree-of-freedom structural model with polynomial nonlinearity, the solution is obtained by means of the moment equation approach in the context of It$\hat{o}$'s stochastic differential calculus. To do so, wind turbulence is idealized as the output of a linear filter excited by a Gaussian white noise. Response statistical moments are computed for both the equivalent linear system and the actual nonlinear one. In the second case, since the moment equations form an infinite hierarchy, a suitable iterative procedure is used to close it. The numerical analyses regard a Duffing oscillator, and the results compare well with Monte Carlo simulation.

• International journal of advanced smart convergence
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• v.4 no.1
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• pp.45-53
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• 2015

This paper is proposed mathematical load modelling based on system identification approach of energy consumption of residential air conditioning. Due to air conditioning is one of the significant equipment which consumes high energy and cause the peak load of power system especially in the summer time. The demand response is one of the solutions to decrease the load consumption and cutting peak load to avoid the reservation of power supply from power plant. In order to operate this solution, mathematical modelling of air conditioning which explains the behaviour is essential tool. The four type of linear model is selected for explanation the behaviour of this system. In order to obtain model, the experimental setup are performed by collecting input and output data every minute of 9,385 BTU/h air-conditioning split type with $25^{\circ}C$ thermostat setting of one sample house. The input data are composed of solar radiation ($W/m^2$) and ambient temperature ($^{\circ}C$). The output data are power and energy consumption of air conditioning. Both data are divided into two groups follow as training data and validation data for getting the exact model. The model is also verified with the other similar type of air condition by feed solar radiation and ambient temperature input data and compare the output energy consumption data. The best model in term of accuracy and model order is output error model with 70.78% accuracy and $17^{th}$ order. The model order reduction technique is used to reduce order of model to seven order for less complexity, then Kalman filtering technique is applied for remove white Gaussian noise for improve accuracy of model to be 72.66%. The obtained model can be also used for electrical load forecasting and designs the optimal size of renewable energy such photovoltaic system for supply the air conditioning.