• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.9
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• pp.23-30
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• 1997

In this paper, a decision feedback recurrent neural equalization (DFRNE) scheme is proposed for adaptive equalization problems. The proposed equalizer models a nonlinear infinite impulse response (IIR) filter. The modified Real-Time recurrent Learning Algorithm (RTRL) is used to train the DFRNE. The DFRNE is applied to both linear channels with only intersymbol interference and nonlinear channels for digital video cassette recording (DVCR) system. And the performance of the DFRNE is compared to those of the conventional equalizaion schemes, such as a linear equalizer, a decision feedback equalizer, and neural equalizers based on multi-layer perceptron (MLP), in view of both bit error rate performance and mean squared error (MSE) convergence. It is shown that the DFRNE with a reasonable size not only gives improvement of compensating for the channel introduced distortions, but also makes the MSE converge fast and stable.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.624-626
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• 1998

Adaptive channel equalization accomplished without resorting to a training sequence is known as blind equalization. In this paper, we present a auto-switching blind, equalization for 8-VSB HDTV receiver. The scheme operate in two mode : blind equalization mode and decision-directed equalization mode. This proposed scheme changes from the blind equalization mode at high error levels to the decision-directed equalization mode at lower error levels smoothly and automatically. Manual switch from the blind equalization mode to the decision-directed mode is not necessary.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5A
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• pp.500-508
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• 2008

Direct-sequence ultra-wideband(DS-UWB) system is being considered as one of promising transmission technologies for wireless personal area networks(WPANs). Due to relatively low spreading factors and huge bandwidth of transmit signal, a DS-UWB receiver needs to be equipped not only with a rake receiver but also with an equalizer, of which the equalizer is not required for traditional direct-sequence code division multiple access(DS-CDMA) systems. The number of rake fingers is limited in practice, influencing the performance of the subsequent equalizer. In this paper, we derive a decision feedback equalizer(DFE) for DS-UWB systems based on the minimum mean square error(MMSE) criterion, and investigate the impact of various parameters on the DFE performance in realistic scenarios. In particular, we propose an approach to improving the performance of the DFE using additional channel estimates for multipaths not combined in the rake receiver, and discuss how the accuracy of channel estimation affects desirable DFE configuration. Moreover, we present simulation results that show the impact of turbo equalization on the DFE performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8C
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• pp.516-521
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• 2011

In this paper, a nonlinear algorithm that maximizes zero-error probability (MZEP) with decision feedback (DF) is proposed to counteract both of severely distorted multi-path fading effect and impulsive noise. The proposed MZEP-DF algorithm has shown the immunity to impulsive noise and the ability of the feedback filter section to cancel the remaining intersymbol interference as well. Compared with the linear MZEP algorithm, it yields above 10 dB enhancement of steady state MSE performance in severely distorted multipath fading channels with impulse noise where the least mean square (LMS) algorithm does not converge below -3dB of MSE.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.3
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• pp.50-59
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• 2014

It has been focused on that the major reasons of aircraft accidents resulted not from human error but from the failure of teamwork or communication in 1980's. Such opinions were suggested in the workshop, so called, "Resource Management on the Flight Deck" by NASA in 1979. The researchers agreed the fact the source of human error was originated from the failure in teamwork, communication or even in leadership of captain. Due to the rapid development of aircraft technologies, the reasons for aircraft accident could be easily found out. According to the analysis results of the technology, most of reasons for the accident might directly be connected not to human error or stick-Rudder skill but to situational awareness, communication, leadership or decision making in the aircraft. This paper has tried to research empirically the satisfaction of flight crews who have gone thorugh CRM training in the commercial airline. Based on the quantitative scale by J. Ford et al. (2014), this paper has proved which characteristics of CRM training has a positive impact on the overall satisfaction of CRM training. It was proven that the teamwork and decision making programs among CRM training have a major effect to the satisfaction level of flight crews.

• Journal of the Korean Society of Marine Environment & Safety
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• v.17 no.2
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• pp.149-154
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• 2011

It is very important for ability to be treated to protect and secure the loss of life and property in emergency situation at sea. 80% of maritime casualty are incurred by human factors rather than a mechanical reason, which means that most maritime incident does not come from only one factor by mistake, but multiple potential factors causing a fault and error. Therefore, after research of the leadership effect to the ship, decision making process and behavior characteristics occurred in emergency situation, this paper presents settlement scheme and strategy in order to reduce human error in the ship.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.2
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• pp.247-252
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• 2015

Adaptive algorithms based on the criterion of zero-error probability (ZEP) have robustness to impulsive noise and their decision feedback (DF) versions are known to compensate effectively for severe multipath channel distortions. However the ZEP-DF algorithm computes several summation operations at each iteration time for each filter section and this plays an obstacle role in practical implementation. In this paper, the ZEP-DF with recursive gradient estimation (RGE) method is proposed and shown to reduce the computational burden of O(N) to a constant which is independent of the sample size N. Also the weight update of the initial state and the steady state is a continuous process without bringing about any propagation of gradient estimation error in DF structure.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.8
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• pp.1037-1045
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• 1999

We propose two new classes of robust blind equalization algorithms against abrupt changes of channel conditions, which we call a triple-mode algorithm(TMA) and an automatic switch-over algorithm(ASA). The conventional DMGSA exhibits slow convergence rates due to the incorrect equalizer tap-updating process under the severe channel conditions. In order to speed up the convergence process, the TMA operates in triple-mode that is based on the dual-mode of the DMGSA incorporated with the tap-updating control modes of the SGA as well as the MSGA. Without resorting to the decision region for selecting the operation mode in the TMA, the ASA automatically switches the blind mode to the smoother conventional decision-directed mode. The ASA uses the error functional that is the weighted sum of the Generalized Sato error and the decision-directed error, where the weights correspond to the channel conditions. Test results on 16-QAM and 8-VSB datas confirm that the TMA and the ASA perform well under the sudden changes of channel conditions.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.8 s.350
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• pp.69-76
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• 2006

In this paper, we propose blind adaptation strategies for decision feedback equalizer (DFE) optimizing the operation mode between acquisitionand tracking modes based on adjustable soft decision devices. The proposed schemes select an optimal soft decision device to generate feedback samples for the DFE at a given noise to signal ratio, and apply corresponding adaptation rules which combine a blind infinite impulse response (IIR) filtering adaptation and the decision-directed least mean squared (DD-LMS) DFE adaptation. These adaptation approaches attempt to achieve not only smooth transition between acquisition and tracking of DFE but also mitigation of error propagation.