• Journal of the Institute of Convergence Signal Processing
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• v.8 no.2
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• pp.91-97
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• 2007

Points of sharp variations in signals are the most important factors when analyzing the features of signals. And in the image, edges include diverse information such as the locations, shape and material. There have been a variety of researches on edge detections, among them, methods based on convolution in the spatial domain have been most popular. However at the early stage of the method, if the noise and many kinds of edges exist in the image, it is not easy to separate edges selectively from corrupted images by noise. In meantime, the wavelet transform for multiscale edge detection is being applied widely to analyze the properties of images in various fields. In this paper, we suggest a robust wavelet-based method, which selectively detects line-edge elements from images in the presence of noise.

• International Journal of CAD/CAM
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• v.9 no.1
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• pp.37-46
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• 2010

Existing methods for the registration of blurred images are efficient for the artificially blurred images or a planar registration, but not suitable for the naturally blurred images existing in the real image mosaic process. In this paper, we attempt to resolve this problem and propose a method for a distortion-free stitching of naturally blurred images for image mosaic. It adopts a multi-resolution and robust feature based inter-layer mosaic together. In each layer, Harris corner detector is chosen to effectively detect features and RANSAC is used to find reliable matches for further calibration as well as an initial homography as the initial motion of next layer. Simplex and subspace trust region methods are used consequently to estimate the stable focal length and rotation matrix through the transformation property of feature matches. In order to stitch multiple images together, an iterative registration strategy is also adopted to estimate the focal length of each image. Experimental results demonstrate the performance of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.9
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• pp.38-46
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• 2000

In this paper, a grating to apply for the optical interconnection is designed using a Genetic Algorithm(GA) as a robust and an efficient schema. A hybrid optical interconnection system architecture is implemented by the liquid crystal panel as a programmable spatial light modulator. As the result of geometrical transformation to obtain the quantitative data for $3{\times}3$ spot beams at CCD array detector by optical experiment truthfully, the mean of beam intensity as a gray level is 202, the maximum value is 225, the minimum value is 186, and a uniformity is quantitatively $1.93{\times}10^{-1}$ similar to simulation result.

• The Korean Journal of Physiology and Pharmacology
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• v.23 no.2
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• pp.131-139
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• 2019

Manually reviewing electroencephalograms (EEGs) is labor-intensive and demands automated seizure detection systems. To construct an efficient and robust event detector for experimental seizures from continuous EEG monitoring, we combined spectral analysis and deep neural networks. A deep neural network was trained to discriminate periodograms of 5-sec EEG segments from annotated convulsive seizures and the pre- and post-EEG segments. To use the entire EEG for training, a second network was trained with non-seizure EEGs that were misclassified as seizures by the first network. By sequentially applying the dual deep neural networks and simple pre- and post-processing, our autodetector identified all seizure events in 4,272 h of test EEG traces, with only 6 false positive events, corresponding to 100% sensitivity and 98% positive predictive value. Moreover, with pre-processing to reduce the computational burden, scanning and classifying 8,977 h of training and test EEG datasets took only 2.28 h with a personal computer. These results demonstrate that combining a basic feature extractor with dual deep neural networks and rule-based pre- and post-processing can detect convulsive seizures with great accuracy and low computational burden, highlighting the feasibility of our automated seizure detection algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.12
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• pp.1671-1677
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• 2018

In this research, the collision detection system based on insect's visual interneuron has been designed. The lobula giant movement detector (LGMD) corresponds to the movement value that increases in direct collision process. If the collision is detected by the LGMD only, it could generate a crash warning even in a non-collision situation, resulting in a lot of false alarms. Directionally sensitive movement detectors (DSMD) are directionally sensitive algorithm based on the elementary movement detectors (EMD) in four directions (up, down, left, and right). In this paper, we propose an efficient VLSI architecture for a realtime collision detection system that is robust to the surrounding environment while improving accuracy. The proposed architecture is synthesized with Dongbu Hightech 110nm standard cell library and shows 333MHz of maximum operating frequency and requires 8400 gates with about 16.5KB of internal memories.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.9
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• pp.58-67
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• 2009

This paper presents a fully digital gain control system with a new high bandwidth and wide dynamic range power detector for DVB-S2 application. Because the peak-to-average power ratio (PAPR) of DVB-S2 system is so high and the settling time requirement is so stringent, the conventional closed-loop analog gain control scheme cannot be used. The digital gain control is necessary for the robust gain control and the direct digital interface with the baseband modem. Also, it has several advantages over the analog gain control in terms of the settling time and insensitivity to the process, voltage and temperature variation. In order to have a wide gain range with fine step resolution, a new AGC system is proposed. The system is composed of high-bandwidth digital VGAs, wide dynamic range power detectors with RMS detector, low power SAR type ADC, and a digital gain controller. To reduce the power consumption and chip area, only one SAR type ADC is used, and its input is time-interleaved based on four power detectors. Simulation and measurement results show that the new AGC system converges with gain error less than 0.25 dB to the desired level within $10{\mu}s$. It is implemented in a $0.18{\mu}m$ CMOS process. The measurement results of the proposed IF AGC system exhibit 80-dB gain range with 0.25-dB resolution, 8 nV/$\sqrt{Hz}$ input referred noise, and 5-dBm $IIP_3$ at 60-mW power consumption. The power detector shows the 35dB dynamic range for 100 MHz input.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.99-108
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• 2015

The embedded microcontroller which is operated by the logic gates synchronized on the clock pulse, is gradually used as main controller of mission-critical systems. Severe electrical situations such as high voltage/frequency surge may cause malfunctioning of the clock source. The tolerant system operation is required against the various external electric noise and means the robust design technique is becoming more important issue in system clock failure problems. In this paper, we propose on-chip backup clock change architecture for the automatic clock failure detection. For the this, we adopt the edge detector, noise canceller logic and glitch-free clock changer circuit. The implemented edge detector unit detects the abnormal low-frequency of the clock source and the delay chain circuit of the clock pulse by the noise canceller can cancel out the glitch clock. The externally invalid clock source by detecting the emergency status will be switched to back-up clock source by glitch-free clock changer circuit. The proposed circuits are evaluated by Verilog simulation and the fabricated IC is validated by using test equipment electrical field radiation noise

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.5
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• pp.574-580
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• 2016

In this paper, we will introduce the system that can control multiple vehicles on the road through Single Board Computers and V2I (Vehicle-To-Infrastructure). Also, we will propose the group evasive maneuver decision algorithm, which plays a critical role in deciding whether the vehicles in the system have to conduct evasive maneuvers to avoid obstacles on the road. In order to test this system, we have utilized Wi-Fi and TCP/IP for establishing the communication between multiple vehicles and the relay server, and observed their driving states on the road with obstacles. During the experiments, we have discovered that our original decision algorithm possesses high failure rate when there is frequency interference in ISM (Industrial Scientific Medical) band. In order to reduce this failure rate, we have implemented the data transition detector. This paper will focus on how the use of data transition detector can affect the reliability of the system under the frequency interference of ISM band. If this technology is improved and applied in the field, we will effectively deal with such dangerous situations as multiple collision accidents through vehicle-to-vehicle communication or vehicle-to-infrastructure communication. Furthermore, this can be applied to the autonomous driving technologies. This can be used as the reference data for the development of the similar system.

• Korean Journal of Optics and Photonics
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• v.17 no.5
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• pp.383-390
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• 2006

The SharkHartmann wavefront sensors are the most popular devices to measure wavefront in the field of adaptive optics. The Shack-Hartmann sensors measure the centroids of spot irradiance distribution formed by each corresponding micro-lens. The centroids are linearly proportional to the local mean slopes of the wavefront defined within the corresponding sub-aperture. The wavefront is then reconstructed from the evaluated local mean slopes. The uncertainty of the Shack-Hartmann sensor is caused by various factors including the detector noise, the limited size of the detector, the magnitude and profile of spot irradiance distribution, etc. This paper investigates the noise propagation in two major centroid evaluation algorithms through computer simulation; 1st order moments of the irradiance algorithms i.e. center of gravity algorithm, and correlation algorithm. First, the center of gravity algorithm is shown to have relatively large dependence on the magnitudes of noises and the shape & size of irradiance sidelobes, whose effects are also shown to be minimized by optimal thresholding. Second, the correlation algorithm is shown to be robust over those effects, while its measurement accuracy is vulnerable to the size variation of the reference spot. The investigation is finally confirmed by experimental measurements of defocus wavefront aberrations using a Shack-Hartmann sensor using those two algorithms.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.7 s.337
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• pp.71-78
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• 2005

A K-Best algerian is known as optimal for implementing the maximum-likelihood detector (MLD), since it has a fixed maximum complexity compared with the sphere decoding or the maximum-likelihood decoding algorithm. However the computational complexity of the K-Best algrithm is still prohibitively high for practical applications when K is large enough. If small value of K is used, the maximum complexity decreases but error flooring at high SNR is caused by error propagation. In this paper, a K-reduction scheme, which reduces K according to each search level, is proposed to solve error propagation problems. Simulations showed that the proposed scheme provides the improved performance in the bit error rate and also reduces the average complexity compared with the conventional scheme.