• 전자공학회논문지 IE
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• v.43 no.1
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• pp.16-24
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• 2006

This paper is aimed to develope of an integrated BCI(Brain Computer Interface System) that make possible for simultaneous multichannel data process and used extra cellular neural activity from the vestibular system instead of electroencephalogram signals for more precision control. The electrical properties pre-amplifier are 47.6 dB of gain, 0.005 % of distortion at 100 Hz, 12M$\Omega$ of input impedance. Window discriminator used two CPU with difference role to increase processing speed so that sampling frequency was 87 kHz. The designed window discriminator has more not only two times in signal resolution power but also ten times in error discrimination power than commericially available discriminator. The proposed method decreases 100 times in amount of integrated data then BCI system during 100 ms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.8
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• pp.1665-1674
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• 2011

In this paper, we proposed an algorithm for speech enhancement of speeches corrupted by colored noise. When there is no correlation between colored noise and speech signal, the colored noise turns into white noise through whitening transformation. This transformed signal has been applied to the generalized subspace approach for speech enhancement. The speech spectral distortion, produced by the whitening transformation as pre-processing, has been restored by using the inverse whitening transformation as post-processing of the proposed algorithm. The performance of the proposed algorithm for speech enhancement has been confirmed by computer simulation. The colored noises used in this experiment were car noise and multi-talker babble. It is confirmed that the proposed algorithm shows better performance from SNR and SSD viewpoint over the previous approach with the data from the AURORA and TIMIT data base.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.4
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• pp.266-271
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• 2007

In mobile channel environments, the effect of the multi-path fading reduces the performance of the mobile communication severely. Previous studies on the effect of the multi-path fading show that, only the channel between fixed base stations and mobile terminals are considered. However, the future mobile communication service such as telematics may use the communication between moving mobile terminals, so called mobile ad-hoc communication, the studies on the channel is required for such situations. In this paper we have measured the mobile channel and analyzed the fading characteristics when using the linear array antennas. In the data measurements, we sent the QPSK modulated signal with carrier frequency of 2GHz band and received the signal using the array antennas equipped on moving vehicles. We have analyzed the fading characteristics and the effects of the fading reduction using the CDF of fading depth using data collected from two moving vehicles. The simulation results show that the beamforming technique adds 6 or 7dB to the fading margin than that of the selection diversity depending on channel environments.

• 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).

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.2
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• pp.245-252
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• 2020

Unexpected equipment defects can cause a huge economic losses in the society at large. Although condition monitoring can provide solutions, the signal processing algorithms must be developed to predict mechanical failures using data acquired from various sensors attached to the equipment. The signal processing algorithms used in a condition monitoring requires high computing efficiency and resolution. To improve condition monitoring on a wireless sensor network(WSN), data visualization can maximize the expressions of the data characteristics. Thus, this paper proposes the extraction of visual feature from temperature data over time using condition monitoring based on a WSN to identify environmental conditions of equipment in a large-scale infrastructure. Our results show that time-frequency analysis can visually track temperature changes over time and extract the characteristics of temperature data changes.

• The Transactions of the Korea Information Processing Society
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• v.7 no.10
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• pp.3290-3299
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• 2000

Digital watermarking has similar concepts with channel coding thechnique for transferring data with minimizing error in noise environment, since it should be robust to various kinds of data manipulation for protecting copyrights of multimedia data. This paper proposes a digital watermarking technique which is robust to various kinds of data manipulation. Intellectual property rights information is encoded using a convolutional code, and block-interleaving technique is applied to prevent successive loss of encoded data. Encoded intelloctual property rithts informationis embedded using spread spectrum technique which is robust to cata manipulation. In order to reconstruct intellectual property rights information, watermark signalis detected by covariance between watermarked image and pseudo rando noise sequence which is used to einbed watermark. Embedded intellectual property rights information is obtaned by de-interleaving and cecoding previously detected wtermark signal. Experimental results show that block interleaving watermarking technique can detect embedded intellectial property right informationmore correctly against to attacks like Gaussian noise additon, filtering, and JPEG compression than general spread spectrum technique in the same PSNR.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.199-205
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• 2021

The distributing board in directly installed on the ground or the bottom surface of the building, and when vibrations such as earthquakes or external shocks occur, the possibility of damage or malfunction of electric components such as internal power devices, wiring, and protection relays increases. Recently, the need for a seismic type distributing board is increasing, and research and development of a distributing board having a vibration damping function and product launch are being conducted. In this paper, an IoT-based data collection device system capable of measuring vibration and environmental data of distributing board was designed and implemented. When vibration occurred on the distributing board, data was stored and visualized in the MySQL DB through Node-RED for monitoring and data storage using the MQTT protocol for reliable messaging transmission. The test was conducted by attaching the IoT device of the distributing board, and data was collected in real-time and monitored through Node-RED.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.216-221
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• 2022

The 4th industrial revolution is accelerating the transition to digital innovation in various aspects of our daily lives, and efforts for manufacturing innovation are continuing in the manufacturing industry, such as smart factories. The 4th industrial revolution technology in manufacturing can be used based on AI, big data, IoT, cloud, and robots. Through this, it is required to develop a technology to establish a production facility data collection and analysis system that has evolved from the existing automation and to find the cause of defects and minimize the defect rate. In this paper, we implemented a system that collects power, environment, and status data from production facility sites through IoT devices, quantifies them in real-time in a cloud computing environment, and displays them in the form of MQTT-based real-time infographics using widgets. The real-time sensor data transmitted from the IoT device is stored to the cloud server through a Rest API method. In addition, the administrator could remotely monitor the data on the dashboard and analyze it hourly and daily.

• Annual Conference of KIPS
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• 2003.05b
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• pp.1269-1272
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• 2003

무선랜은 무선으로 근거리 단말들을 연결하는 통신 기술로, 높은 데이터 전송률을 제공할 수 있다. 무선랜은 보통 하나의 AP와 하나 이상의 단탈 기기가 BSS를 구성하는데 AP에서 거리가 멀리 떨어진 단말은 신호의 세기가 약해지므로 고속 데이터 전송률의 보장을 반을 수 없는 단점을 가지고 있다. 본 논문에서는 무선 단말중 일부를 리피터로 이용함으로써 그룹화를 통해 고속 데이터 전송을 가능하게 하는 방법을 제안하고, 시뮬레이션을 통해 무선 단말의 그룹화를 위한 깊이우선탐색 알고리즘과 넓이우선탐색 알고리즘을 비친, 분석하였다. 그 결과 넓이우선탐색 알고리즘이 무선 단말을 위한 그룹화에 보다 효과적인 알고리즘임을 보였다.

• Annual Conference of KIPS
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• 2014.04a
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• pp.995-997
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• 2014

뇌파는 최근에 가장 많이 연구되고 있는 생체신호이다. 본 연구에서는 오픈 감정뇌파데이터인 DEAP Dataset를 활용한 데이터 분석 실험을 시행하였다. DEAP Dataset는 총 32개의 데이터이며, 32채널로 구성되어 있다. 전처리 과정에서는 디지털 필터인 IIR(Infinite Impulse Response) Filter를 사용하여 잡음을 제거하였고, 인공산물인 안구잡파(EOG: Electrooculograms) 제거에는 LMS(the Least Mean squares) 알고리즘을 사용하였다. 감정분류는 Valence-Arousal 평면을 사용하여 네 개의 감정으로 구분하였고, 분류 실험으로는 패턴인식 알고리즘인 SVM(support Vector Machine)를 사용하였다. 실험결과 SVM이 70%대의 결과를 도출하여 이전 실험결과보다 높은 정확도를 도출하였다.