• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.31-32
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• 2014

• Journal of Navigation and Port Research
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• v.28 no.6
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• pp.509-515
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• 2004

The aim of this paper is to forecast passenger numbers and freight volumes in 2005 and it is proposed optimal tonnage of passenger ship. The forecasting of passenger numbers and freight volumes is important problem in order to determine optimal tonnage of passenger ship, port plan and development. In this paper, the forecasting of passenger numbers and freight volumes are performed by the method of neural network using back-propagation learning algorithm. And this paper compares the forecasting performance of neural networks with moving average method and exponential smooth method As the result of analysis. The forecasting of passenger numbers and freight volumes is that the neural networks performed better than moving average method and exponential smoothing method on the basis of MSE(mean square error) and MAE(mean absolute error).

• Journal of IKEEE
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• v.10 no.1 s.18
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• pp.69-74
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• 2006

In this paper, we present symbol detection methods for decision feedback equalizers (DFE) in trellis coded modulation systems. The proposed symbol detectors improve symbol error rate (SER) by exploiting the coding structure of trellis coded modulation (TCM). For example, for 8-PAM signals the achieved SER with the proposed detection scheme is improved to $2{\times}10^{-5}$ from $2.5{\times}10^{-2}$ of the conventional symbol-by-symbol detector under AWGN channel at 20dB SNR. This SER improvements mitigate error propagation of DFE.and produces significant over-all SER improvement for under multipath channels (for example, from 0.26 to 0.01 and 0.005 under a severe multipath channel 20dB SNR as shown in the simulation result of this paper).

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.2
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• pp.170-177
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• 2009

The objective of this study is to evaluate an acoustic emission (AE) source characterization and fracture behavior of the SM45C steel by using back-propagation neural network (BPN). In previous research Ref. [8] about k-nearest neighbor classifier (k-NNC) continuity, we used K-means clustering method as an unsupervised learning method for obtaining multi-variate AE main data sets, such as AE counts, energy, amplitude, risetime, duration and counts to peak. Similarly, we applied k-NNC and BPN as a supervised learning method for obtaining multi-variate AE working data sets. According to the error of convergence for determinant criterion Wilk's ${\lambda}$, heuristic criteria D&B(Rij) and Tou values are discussed. As a result, in k-NNC before fracture signal is detected or when fracture signal is detected, showed that produce some empty classes in BPN. And we confirmed that could save trouble in AE signal processing if suitable error of convergence or acceptable encoding error give to BPN.

• ETRI Journal
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• v.26 no.2
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• pp.101-111
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• 2004

This paper presents a near-optimum blind decision feedback equalizer (DFE) for the receivers of Advanced Television Systems Committee (ATSC) digital television. By adopting a modified trellis decoder (MTD) with a trace- back depth of 1 for the decision device in the DFE, we obtain a hardware-efficient, blind DFE approaching the performance of an optimum DFE which has no error propagation. In the MTD, the absolute distance is used rather than the squared Euclidean distance for the computation of the branch metrics. This results in a reduction of the computational complexity over the original trellis decoding scheme. Compared to the conventional slicer, the MTD shows an outstanding performance improvement in decision error probability and is comparable to the original trellis decoder using the Euclidean distance. Reducing error propagation by use of the MTD in the DFE leads to the improvement of convergence performance in terms of convergence speed and residual error. Simulation results show that the proposed blind DFE performs much better than the blind DFE with the slicer, and the difference is prominent at the trellis decoder following the blind DFE.

• Journal of KIISE:Information Networking
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• v.30 no.6
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• pp.755-763
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• 2003

To improve performance over noisy wireless channels, mobile wireless networks employ forward error correction(FEC) techniques. The performance of static FEC algorithms, however, degrades by poorly matching the overhead of their correction code to the degree of the fluctuating underlying channel error. This paper proposes an adaptive FEC technique called FECA(FEC-level Adaptation), which dynamically tunes FEC strength to the currently estimated channel error rate at the data link layer. FECA is suitable for wireless networks whose error rate is high and slowly changing compared to the round-trip time between two communicating nodes. One such example network would be a sensor network in which the average bit error rate is higher than $10^{-6}$ and the detected error rate at one time lasts a few hundred milliseconds on average. Our experiments show that FECA performs 15% in simulations with theoretically modeled wireless channels and in trace-driven simulations based on the data collected from real sensor networks better than any other static FEC algorithms.

• Journal of Mechanical Science and Technology
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• v.16 no.7
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• pp.935-941
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• 2002

This work is to investigate the combustion characteristics and flame propagation of the LPG (liquified petroleum gas) and gasoline fuel. In order to characterize the combustion processes of the fuels, the flame propagation and combustion characteristics were investigated by using a constant volume combustion chamber The flame propagation of both LPG and gasoline fuels was investigated by the laser deflection method and the high-speed Schlieren photography. The result of laser deflection method show that the error of measured flame propagation speed by laser method is less than 5% compared with the result of high-speed camera. The flame propagation speed of the fuel is increased with the decrease of initial pressure and the increase of initial temperature in the constant volume chamber. The results also show that the equivalence ratio has a grate effect on the flame speed, combustion pressure and the combustion duration of the fuel-air mixture.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12C
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• pp.753-758
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• 2011

The constant modulus algorithm (CMA) widely used in blind equalization applications minimizes the averaged power of constant modulus error (CME) defined as the difference between an instant output power and a constant modulus. In this paper, a decision feedback version of the linear blind algorithm based on maximization of the zero-error probability for CME is proposed. The Gaussian kernel of the maximum zero-error criterion is analyzed to have the property to cut out excessive CMEs that may be induced from severely distorted channel characteristics. Decision feedback approach to the maximum zero-error criterion for CME is developed based on the characteristic that the Gaussian kernel suppresses the outliers and this prevents error propagation to some extent. Compared to the linear algorithm based on maximum zero-error probability for CME in the simulation of blind equalization environments, the proposed decision feedback version has superior performance enhancement particularly in cases of severe channel distortions.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.513-518
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• 1987

In this paper the error equations of the SDINS aligned by the gyrocompass are derived considering that the alignment errors are correlated to the sensor errors. Also the navigation errors due to the correlated errors are simulated by this error equations. The simulations are performed by the covariance analysis method, assumed all the sensor errors are random constants. The simulation results show that while the INS maintains the alignment attitude the cancellation takes place between the correlated errors, but once the INS changes attitude this cancellation effect is perturbed.

• Journal of Biomedical Engineering Research
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• v.11 no.1
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• pp.89-96
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• 1990

The numerical evaluation of Rayleigh's integral for the sound source reconstruction can be speeded up by the use of angular frequency propagation method and the FFT. However, are several source of errors involved during the reconstruction. Besides the aliasing error due to undersampling in space, the wrap around error. which is caused by undersampling the kernel functionin frequency domain, and windowing effect are present. We found that there is no replicated source problem and the windowing effect is due to the windowing the kernel function In frequency domain, and, xero padding is always required to improve the quality of reconstruction.