• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.399-402
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• 2000

In this paper, we present a regularized mixed norm multichannel image restoration algorithm. The problem of multichannel restoration using both within- and between- channel deterministic information is considered. For each channel a functional which combines the least mean squares (LMS), the least mean fourth(LMF), and a smoothing functional is proposed, We introduce a mixed norm parameter that controls the relative contribution between the LMS and the LMF, and a regularization parameter that defines the degree of smoothness of the solution, both updated at each iteration according to the noise characteristics of each channel. The novelty of the proposed algorithm is that no knowledge of the noise distribution for each channel is required, and the parameters mentioned above are adjusted based on the partially restored image.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.6
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• pp.653-657
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• 2015

A new paired gate-source voltage RF capacitance-voltage (C-V) method of extracting the effective channel length and parasitic capacitance using the intersection between two closely spaced linear regression lines of the gate capacitance versus gate length measured from S-parameters is proposed to remove errors from conventional C-V methods. Physically verified results are obtained at the gate-source voltage range where the slope of the gate capacitance versus gate-source voltage is maximized in the inversion region. The accuracy of this method is demonstrated by finding extracted value corresponding to the metallurgical channel length.

• Journal of Korea Multimedia Society
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• v.20 no.1
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• pp.32-42
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• 2017

This paper proposes a new haze removal method for moving image sequence. Since the conventional dark channel prior haze removal method adjusts each color component separately in RGB color space, there can be severe color distortion in the haze removed output image. In order to resolve this problem, this paper proposes a new haze removal scheme that adjusts luminance and saturation components in HLS color space while retaining hue component. Also the conventional dark channel prior haze removal method is developed to obtain best haze removal performance for a single image. Therefore, if it is applied to a moving image sequence, the estimated parameter values change rapidly and the haze removed output image sequence shows unnatural glitter defects. To overcome this problem, a new parameter estimation method using Kalman filter is proposed for moving image sequence. Experimental results demonstrate that the haze removal performance of the proposed method is better than that of the conventional dark channel prior method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.835-837
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• 2012

In this paper, we have been analyzed conduction path by device parameter of double gate(DG) structure that have top gate and bottom gate. The Possion equation is used to analytical. The change of conduction path have been investigated for various channel lengths, channel thickness and gate oxide thickness using this model, given that these parameters are very important in design of DGMOSFET. The optimum channel doping concentration is determined as the deviation of conduction path is considered according to channel doping concentration.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.272-282
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• 2004

This paper introduces a regularized mixed norm multi-channel image restoration algorithm using both within-and between- channel deterministic information. For each channel a functional which combines the least mean squares (LMS), the least mean fourth (LMF), and a smoothing functional is proposed. We introduce a mixed norm parameter that controls the relative contribution between the LMS and the LMF, and a regularization parameter defining the degree of smoothness of the solution, where both parameters are updated at each iteration according to the noise characteristics of each channel. The novelty of the proposed algorithm is that no knowledge of the noise distribution for each channel is required and that the parameters mentioned above are adjusted based on the partially restored image.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.9
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• pp.24-29
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• 2010

This paper presents the RF modeling for silicon nanowire MOSFET with 30 nm channel length and 5 nm channel radius. Equations for analytical parameter extraction are derived by analysis of Y-parameter. Accuracies of the new model and extracted parameters have been verified by 3-dimensional device simulation data up to 100 GHz. The model verifications are performed under conditions of saturation region ($V_{gs}$ = $_{ds}$ = 1 V) and linear region ($V_{gs}$ = 1 V, $V_{ds}$ = 0.5 V). The RMS modeling error of Y-parameters was calculated to be 1 %.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2A
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• pp.110-118
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• 2006

In part-I of the paper, two sub-channel structures, either contiguous or distributed, were considered. Modeling the SNR distribution over a sub-channel as Ricean in general, the statistical chracteristics were investigated. In this part of the paper, we develop a generalized two step channel/resource allocation algorithm, which incorporates the two statistical measurements, and analyze the spectral efficiency of OFDMA in terms of average frequency utilization for the two sub-channel structures. In OFDMA with distributed structure, the key design parameter would be the sub-channel bandwidth. To give an insight into the impact on this parameter, we show in the numerical results the frequency utilization as a function of sub-channel bandwidth normalized to coherence bandwidth. As confirmed by numerical results, for contiguous sub-channel structure, we obtain the nominal multiuser diversity gain when the sub-channel bandwidth is smaller than the coherence bandwidth and lose the gain as it is getting larger.

• ETRI Journal
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• v.27 no.3
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• pp.330-333
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• 2005

The Inter-Channel Level Difference (ICLD) is a cue parameter to estimate spectral information in a binaural cue coding that has been recently in the spotlight as a multichannel audio signal compression technique. Even though the ICLD is an essential parameter, it is generally distorted by quantization. In this paper, a new modified ICLE representation method to minimize the quantization distortion is proposed by adopting a flexible determination of the reference channel and the unidirectional quantization. Our experimental result confirms that the proposed method improves the multichannel audio output quality even with the reduced bit-rate.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2745-2748
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• 2003

In this paper, we implement the photoplethysmo-graphy system that have three channel pulse wave detects and one channel ECG amplifier. In order to detect the artery state, we measured the pulse waves at different positions, simultaneously. In general, arterial vascular system suffers the decrease of compliance, increase of resistance, and decrease of distensibility through aging. Therefore, we compared and analyzed variation of tile Pulse waves parameter both in time and frequency domains that is concerned with the changes of arterial characteries. And then evaluated the correlation coefficients between the parameters variation and the age group. As the result of experiment, we found that the Parameters have a significant correlation about aging.

• Journal of information and communication convergence engineering
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• v.8 no.3
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• pp.267-272
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• 2010

For the last decade, recurrent neural networks (RNNs) have been commonly applied to communications channel equalization. The major problems of gradient-based learning techniques, employed to train recurrent neural networks are slow convergence rates and long training sequences. In high-speed communications system, short training symbols and fast convergence speed are essentially required. In this paper, the derivative-free Kalman filter, so called the unscented Kalman filter (UKF), for training a fully connected RNN is presented in a state-space formulation of the system. The main features of the proposed recurrent neural equalizer are fast convergence speed and good performance using relatively short training symbols without the derivative computation. Through experiments of nonlinear channel equalization, the performance of the RNN with a derivative-free Kalman filter is evaluated.