• Journal of the Institute of Convergence Signal Processing
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• v.8 no.2
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• pp.130-135
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• 2007

This paper deals with a controller design for a 2 dimensional aeroelatic model which has unknown parameters including polynomial type nonlinearity. Actually in case of state and acuator signal having magnitude, rate and bandwidth limitations, the controller can't be implemented and so in each case, a filter is used for implementation. First, error signals are defined upon the backstepping theory, and tracking error signals are also defined due to command signal and filter signals and then compensated tracking error signals are defined. Lastly, a Lyapunov function is defined for the stabilization and from this method, an adaptive law is derived. Simulations are done for the demonstrtion of the effectiveness of the algorithms.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.142-149
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• 2015

Most of the mono-camera based lane detection systems are fragile on poor illumination conditions. In order to compensate limitations of single sensor utilization, lane information fusion system using multiple lane sensors is an alternative to stabilize performance and guarantee high precision. However, conventional fusion schemes, which only concerns object detection, are inappropriate to apply to the lane information fusion. Even few studies considering lane information fusion have dealt with limited aids on back-up sensor or omitted cases of asynchronous multi-rate and coverage. In this paper, we propose a lane information fusion scheme utilizing multiple lane sensors with different coverage and cycle. The precise lane information fusion is achieved by the proposed fusion framework which considers individual ranging capability and processing time of diverse types of lane sensors. In addition, a novel lane estimation model is proposed to synchronize multi-rate sensors precisely by up-sampling spare lane information signals. Through quantitative vehicle-level experiments with around view monitoring system and frontal camera system, we demonstrate the robustness of the proposed lane fusion scheme.

• Journal of the Korea Convergence Society
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• v.7 no.3
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• pp.77-85
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• 2016

We propose a digital signal processing technic that can compensate the non-linearity inherent in audio amplifiers, and present the result of the simulation. The inherent non-linearity of the audio power amplifier arising from analog devices is compensated via a digital signal processing technic consisting of indirect learning architecture and an adaptive filter. The simulation results show that the compensator can be realized using a third-order polynomial and compensates odd-order non-linearity efficiently. The even-oder non-linearity is mainly due to the dc offset at the output, which is difficult to eliminate with the proposed method. Care must be taken in designing the bias circuit to avoid the DC offset at the output. The proposed technic has significance in that digital signal processing technic can compensate for the impairment that is an inherent characteristic of an analog system.

• Journal of Convergence for Information Technology
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• v.9 no.5
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• pp.125-129
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• 2019

This paper describes the jamming effect of phase-coded pulse compression(PCPC) radar. Barker code radar, a typical PCPC radar, separates transmission pulses into 13 or 31 small pulses and phase modulates and transmits each pulse signal to increase radar detection efficiency and reduce the influence of jamming. Generally, when the radar is subjected to jamming, the detection distance becomes shorter and the detection error rate becomes higher. In the case of noise jamming or carrier jamming on the PCPC radar, the jamming effect is very small for no phase-coded convergence. However, the jamming effect is large in the case of synchronous jamming using the pulse-coded signal as a jamming signal with DRFM. It can be seen that the jamming effect increases when the storage time of the pulse-coded signal is prolonged. This study is considered to be useful for PCPC radar and EW jamming system design.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.1
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• pp.9-18
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• 2021

Although Generative Adversarial Networks (GANs) have gained great popularity in computer vision and related fields, generating audio signals independently has yet to be presented. Unlike images, an audio signal is a sampled signal consisting of discrete samples, so it is not easy to learn the signals using CNN architectures, which is widely used in image generation tasks. In order to overcome this difficulty, GAN researchers proposed a strategy of applying time-frequency representations of audio to existing image-generating GANs. Following this strategy, we propose an improved method for increasing the fidelity of synthesized audio signals generated by using GANs. Our method is demonstrated on a public speech dataset, and evaluated by Fréchet Inception Distance (FID). When employing our method, the FID showed 10.504, but 11.973 as for the existing state of the art method (lower FID indicates better fidelity).

• Journal of the Korea Convergence Society
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• v.6 no.6
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• pp.177-183
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• 2015

The image information acquired by a model submarine is transmitted through the repeater. The control signal of a position for submarine and its speed is also controlled by the repeater. Shooting images of underwater circumstances are transmitted to the repeater where the received signal controls a position and speed of underwater submarine. This repeater is combined by a buoy that is floating on the surface to relay the signal of image as well as control between a control unit and a submarine whereas the repeater communicates wirelessly with a control unit. Due to wire communication between the repeater and the submarine, the underwater exploration can be smoothly carried out without a risk of loss of a model submarine. Also, connecting to the repeater and control unit wirelessly makes it possible to conduct easily the underwater exploration. The convergence technology that combines a wireless communication and a control as well as a model submarine is designed.

• Journal of the Korea Convergence Society
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• v.8 no.7
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• pp.75-84
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• 2017

The purpose of this study is to find the relation between the detailed categories of the self-efficacy of workers in the field of railroad signaling and the detailed categories of their fatigue in the use of analysis of moment structure(AMOS) model. A self-administered questionnaire survey of workers in the field of railroad signaling had been conducted and a total of 341 copies were analyzed. This study had the assumption that their general self-efficacy and social self-efficacy would negatively influence their physical fatigue and mental fatigue. As a result, their general self-efficacy negatively influenced their physical fatigue and mental fatigue, whereas their social self-efficacy didn't influence their physical fatigue and mental fatigue. Therefore, it is possible to reduce the fatigue of the study subjects by enhancing corporate support to increase their general self-efficacy.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.132-137
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• 2004

In this paper, the adaptive noise canceler using neural network with backpropagation is designed. The adaptive noise canceler using the least mean square algorithm has the large correlativity of the reference signal. The performance of the adaptive noise canceler shows the limitation when the information signal is relatively small to the noise. The system proposed in this paper plays an important role in denoising these signals. In addition, the experiments are carried out to analyze the effects of the number of hidden layers and nodes about the system. The performance of the proposed adaptive noise canceler is compared with that of the system which is used the least mean square algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.33-38
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• 2005

Degradation is generated by several causes in the process of digitalization or transmission of data. And its essential cause is noise. Therefore, researches for wavelet-based methods which reconstruct signal degraded by noise have continued. In AWGN(addtive white gaussian noise) environment, the general trend for denoising is to use the thresholding method. Reconstructed signal includes a lot of noise because these methods only consider statistical characteristic regarding noise. In this paper, we present a new method which uses the cumulation of wavelet detail coefficients. As a result, reconstruction of edges and denoising performance are improved. Also we compare existing methods using SNR(signal-to-noise ratio) as the standard of judgement of improvemental effect.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.62-66
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• 2011

This paper proposes a parallel architecture of random signal-based learning (PRSL), merged with simulated annealing (SA), to optimize the fuzzy logic controller (FLC). Random signal-based learning (RSL) finds the local optima very well, whereas it can not finds the global optimum in a very complex search space because of its serial nature. To overcome these difficulties, PRSL, which consists of serial RSL as a population, is considered. Moreover, SA is added to RSL to help the exploration. The validity of the proposed algorithm is conformed by applying it to the optimization of a FLC for the inverted pendulum.