• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.6
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• pp.1447-1452
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• 1996

In this papre, a complex fuzzy adaptive decision feedback equalizer using the RLS algorithm is proposed. The proposed equalizer is based on the complex fuzzy adaptive equalizer. The 'IF'-part of the complex fuzzy adaptive decision feedback equalizer has membership functions which are characterized by the sate of decision feedback. The role of decision feedback is to reduce the computational complexity. Computer simulation shows that the proposed equalizer not only reduces the computational complexity but also improves the performance compared with the conventional complex fuzzy adaptive equalizers under the assumption of perfect knowledge of the linear and nonlinear channels. The effects of error propagation due to wrong decision feedback is also shown.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.271-274
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• 1996

In this paper a new determination scheme of linear decision function is proposed. In this scheme, the weights in linear decision function is obtained by genetic algorithm. The result considering balance between clusters as well as classification error can be obtained by properly selecting the fitness function of genetic algorithm in determination of linear decision function and this has the merit in applying this scheme to the construction of binary decision tree. The proposed scheme is applied to the artificial two dimensional data and real multi dimensional data. Experimental results show the usefulness of the proposed scheme.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.4
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• pp.21-31
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• 2020

There are two to three helicopter accidents every year in Korea, representing 5.7 deaths per 100,000 flights. In this study, an analysis was conducted on helicopter accidents that occurred in Korea from 2005 to 2017. The accident analysis was based on the aircraft accident and incident report published by the Aircraft and Railway Accident Investigation Board. This Research analyzed the characteristics of accidents occurring in Korea caused by human error by pilots. Accident analysis was done by classifying the organization, flight mission, aircraft class, flight stage, accident cause, etc. Pilot's huan error was classified as Skill-based error, decision error and perceptual error in accordance with the HFACS taxonomy. The accidents caused by pilot's human error were classified into five categories: powerlines collision, loss of control, fuel exhaustion, unstable approach to reservoir, and elimination of tail rotor.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.49-55
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• 2016

In digital forensic images, there is a serious problem that is distributed with various image types. For the problem solution, this paper proposes a classification algorithm of the forensic image types. The proposed algorithm extracts the 21-dim. feature vector with the contrast and energy from GLCM (Gray Level Co-occurrence Matrix), and the entropy of each image type. The classification test of the forensic images is performed with an exhaustive combination of the image types. Through the experiments, TP (True Positive) and FN (False Negative) is detected respectively. While it is confirmed that performed class evaluation of the proposed algorithm is rated as 'Excellent(A)' because of the AUROC (Area Under Receiver Operating Characteristic Curve) is 0.9980 by the sensitivity and the 1-specificity. Also, the minimum average decision error is 0.1349. Also, at the minimum average decision error is 0.0179, the whole forensic image types which are involved then, our classification effectiveness is high.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.1-7
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• 2010

In this paper, the performance of the soft-decision-and-forward (SDF) protocol in the cooperative communication network with one source, one relay, and one destination, where each node has two transmit and receive antennas, is analyzed in terms of the bit error rate (BER) obtained from the pairwise error probability (PEP). For the slow-varying Rayleigh fading channel, the optimal and suboptimal power allocation ratios are determined without feedback. The optimal power allocation can be obtained by minimizing the average PEP. For the tractability, an alternative strategy of maximizing the product SNR of direct and relay links, which we call the suboptimal power allocation, is considered. Through the numerical analysis, we show that the performance gap between the suboptimal and the optimal power allocation is negligible in the high SNR region.

• 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).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.6
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• pp.540-549
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• 2013

An adaptive non-uniform quantization scheme is proposed for soft-decision error correction in NAND flash memory. Even though the conventional maximizing mutual information (MMI) quantizer shows the optimal post-FEC (forward error correction) bit error rate (BER) performance, this quantization scheme demands heavy computational overheads due to the exhaustive search to find the optimal parameter values. The proposed quantization scheme has a simple structure that is constructed by only six parameters, and the optimal values of them are found by maximizing the mutual information between the input and the output symbols. It is demonstrated that the proposed quantization scheme improves the BER performance of soft-decision decoding with only small computational overheads.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.617-627
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• 2021

Underwater Acoustic Channels (UAC) have inherent sparse characteristics. The traditional adaptive equalization techniques do not utilize this feature to improve the performance. In this paper we consider the Variable Adaptive Subgradient Projection (V-ASPM) method to derive a new sparse equalization algorithm based on the Minimum Symbol Error Rate (MSER) criterion. Compared with the original MSER algorithm, our proposed scheme adds sparse matrix to the iterative formula, which can assign independent step-sizes to the equalizer taps. How to obtain such proper sparse matrix is also analyzed. On this basis, the selection scheme of the sparse matrix is obtained by combining the variable step-sizes and equalizer sparsity measure. We call the new algorithm Sparse-Control Proportional-MSER (SC-PMSER) equalizer. Finally, the proposed SC-PMSER equalizer is embedded into a turbo receiver, which perform turbo decoding, Digital Phase-Locked Loop (DPLL), time-reversal receiving and multi-reception diversity. Simulation and real-field experimental results show that the proposed algorithm has better performance in convergence speed and Bit Error Rate (BER).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.77-82
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• 2018

This paper is concerned with the performance analysis of a modified stop-and-go generalized multi-modulus algorithm (MSAG-GMMA) adaptive blind equalization algorithm with variable step size. The proposed algorithm multiplies the fixed step size by the error signal of the decision-oriented algorithm in the equalization coefficient update equation, and changes the step size according to the error size. Also, the MSAG-GMMA having a fixed step size is operated so as to maintain a fast convergence speed from a certain threshold to a steady state by determining the error signal size of the decision-directed algorithm, and when the MSAG-GMMA to work To evaluate the performance of the proposed algorithm, we use the ensemble ISI, ensemble-averaged MSE, and equalized constellation obtained from the output of the equalizer as the performance index. Simulation results show that the proposed algorithm has faster convergence speeds than MMA, GMMA, and MSAG-GMMA and has a small residual error in steady state.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.53-58
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• 2020

This paper is concerned with the performance analysis of MSAGF-MMA with variable step size whose step size varies according to input power signal and decision-directed error signal. The proposed algorithm is made to change according to the input power signal which can reliably increase the convergence speed to the steady state by making the step size less affected by the fluctuation of the input signal in the MMA having the binary flag obtained from the modified Stop-and-Go algorithm. At the same time, the step size can be varied according to the decision-directed error signal so that the residual error can be reduced in the steady state. As a result of computer simulations, it is confirmed that the proposed algorithm has a very good performance in the evaluation of residual ISI and averaged-MSE in steady state as well as in terms of convergence speed to steady state compared to MMA and MSAGF-MMA.