• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.12
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• pp.90-96
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• 2008

Recently, various recording technologies are studied for optical data storage. After standardization of BD (Blu-ray Disc) and HD-DVD (High-Definition Digital Versatile Disc), the industry is looking for a suitable technology for next generation optical data storage. Super-RENS (Super-Resolution Near Field Structure) technique, which is capable of compatibility with other systems, is one of next optical data storage. In this paper, we proposed a neural network-based nonlinear equalizer (NNEQ) for Super-RENS discs. To mitigate the nonlinear ISI (Inter-Symbol Interference), we applied NARX (Nonlinear AutoRegressive eXogenous) which is a kind of neural networks. Its validity is tested with the RF signal samples obtained from a Super-RENS disc. The performance of the proposed equalizer is superior to the one without equalization and that of the Limit-EQ in terms of BER (Bit Error Rate).

• Journal of Korea Multimedia Society
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• v.14 no.11
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• pp.1392-1400
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• 2011

In most digital imaging applications, high-resolution images or videos are usually desired for later image processing and analysis. The image signal obtained from general imaging system occurs image degradation during the process of image acquirement caused by the optics, physical constraints and the atmosphere effects. Super-resolution reconstruction, one of the solution to address this problem, is image reconstruction technique that produces a high-resolution image from several low-resolution frames in video sequences. In this paper, we propose an improved super-resolution method using Projection onto Convex Sets (POCS) method based on Shift & Add (S&A). The image using conventional algorithms is sensitive to noise. To solve this problem, we propose a fusion algorithm of S&A and POCS. Also we solve the problem using BLPF (Butterworth Low-pass Filter) in frequency domain as optical blur. Our method is robust to noise and has sharpness enhancement ability. Experimental results show that the proposed super-resolution method has better resolution enhancement performance than other super-resolution methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.129-136
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• 2011

This paper presents the coding method that have multi-mode and efficiency of audio codecs using the feature of audio signal. Recently, the developed extension super-wideband codec based on G.718 wideband divides two mode between Generic and Sinusiodal. So codec efficently encode audio signal exist in super-wideband. But the codec is not as efficent coding for harmonic component of wind instrument and string instrument and individual-Line component of percussion instrument. The proposed method are modeling and encoding multiple pitch and individual-line feature using multi mode coding. For the performance evaluation, we used SNR in MDCT domain for objective test and MUSHRA test for subjective test. As a result, the performance of SNR and MUSHRA test of the proposed method have better performance than the G.718 super-wideband codec.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.3
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• pp.252-255
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• 2014

In the case of long-stator linear drives, unlike rotative drives for which speed or position sensors are a single unit attached to the shaft, these sensors extend along the guideway. The position signal transmitted from maglev vehicle can't meet the need of the real-time propulsion control. In this paper the position estimator for propulsion inverter driving long stator linear synchronous motor (LSLSM) in high speed maglev train is proposed. In order to get the higher resolution of the position information transmitted from vehicle, Full order state observer is proposed for position estimator.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.219-222
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• 2002

There are screw, reciprocating type turbo compressor by structure in an air compressor which is essential equipment on the industrial spot. Recently, the application range of a turbo compressor tend to be wide gradually. And this type of compressor needs high speed rotation of impeller in structure so high ratio gearbox and conventional induction motor driving required. This mechanical system have results of increased moment of inertia and mechanical friction loss. Recent studies of modern turbo compressor have been applied to developing super high speed BLDC motor and driver which remove gearbox that make its size small and mechanical friction loss minimum. To accomodate this tendency, we tried to develope a super high speed motor drive system for 150Hp, 70,000rpm direct drive Turbo compressor using DSP(Digital Signal Processor) and SVPWM(Space Vector Modulation PWM) technique. The results of this specific application show that super high speed driver and controller could be implemented well with digital electronics.

• ETRI Journal
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• v.32 no.3
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• pp.390-394
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• 2010

In this paper, we propose a new super-resolution technique based on interpolation of the high-frequency subband images obtained by discrete wavelet transform (DWT) and the input image. The proposed technique uses DWT to decompose an image into different subband images. Then the high-frequency subband images and the input low-resolution image have been interpolated, followed by combining all these images to generate a new super-resolved image by using inverse DWT. The proposed technique has been tested on Lena, Elaine, Pepper, and Baboon. The quantitative peak signal-to-noise ratio (PSNR) and visual results show the superiority of the proposed technique over the conventional and state-of-art image resolution enhancement techniques. For Lena's image, the PSNR is 7.93 dB higher than the bicubic interpolation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9C
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• pp.820-825
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• 2007

Super-orthogonal space-time trellis code (SOTTC) uses the expanded set of the orthogonal space-time block code to obtain coding gain and diversity gain without loss of transmit rate. In SOSTTCs, signal set expansions are performed by rotating the first column of the code matrix. The rotating phases used previously were selected to avoid the signal constellation expansion rather than the performance improvement. In this paper, we make a design criterion to select the proper rotating phase to improve the performance of SOSTTCs for fast Rayleigh fading channels. In addition, we design improved SOSTTCs by using the proper rotating phase. Simulation results are also provided to confirm our SOSTTCs are superior to the previous SOSTTCs in the view of BER performance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.5 no.3 s.11
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• pp.29-39
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• 2006

In this paper, we propose an efficient method to detect the signal and evaluate performance of the system in frequency selective fading channel. We combine proposed system with OFDM (Orthogonal Frequency Division Multiplexing) to improve performance of the system. First, we study the SOSTTC-OFDM system using two transmit antenna and one receive antenna, and compare performance of the proposed space-time coded OFDM with that of previous system. We expand this system to the system using four transmit antennas with the proposed decoding method. Simulation results show that the proposed decoding method can detect the signal efficiently, and we identify that the performance of the proposed system is shown with varying doppler frequency in frequency selective fading channel.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.1
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• pp.8-14
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• 2022

With the development of deep learning, super-resolution (SR) methods have tried to use deep learning mechanism, instead of using simple interpolation. SR methods using deep learning is generally based on convolutional neural networks (CNN), but recently, SR researches using attention mechanism have been actively conducted. In this paper, we propose an approach of improving SR performance using one of the attention mechanisms, non-local sparse attention (NLSA). Through experiments, we confirmed that the performance of the existing SR models, IMDN, CARN, and OISR-LF-s can be improved by using NLSA.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.160-165
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• 2022

Mutual distillation is a knowledge distillation method that guides a cohort of neural networks to learn cooperatively by transferring knowledge between them, without the help of a teacher network. This paper aims to confirm whether mutual distillation is also applicable to super-resolution networks. To this regard, we conduct experiments to apply mutual distillation to the discriminators of SRGANs and analyze the effect of mutual distillation on improving SRGAN's performance. As a result of the experiment, it was confirmed that SRGANs whose discriminators shared their knowledge through mutual distillation can produce super-resolution images enhanced in both quantitative and qualitative qualities.