• Journal of Korea Multimedia Society
• /
• v.20 no.11
• /
• pp.1842-1848
• /
• 2017

Recently, user motion estimation methods using various wearable devices have been actively studied. In this paper, we propose a motion estimation system using Myo, which is one of the wearable devices, using two Myo and their dependency relations. The estimated motion is used as a command for remotely controlling the robot. Myo's Orientation and EMG signals are used for motion estimation. These two type data sets are used complementarily to increase the accuracy of motion estimation. We design and implement the system according to the proposed method and analyze the results through experiments. As a result of comparison with previous studies, the accuracy of motion estimation can be improved by about 12.3%.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.94-98
• /
• 2009

In this paper, we propose a new channel estimation scheme for amplify and forward cooperative diversity with relay selection. In order to select best relay, it is necessary to know channel state information (CSI) at the destination. Most of the previous works, however, assume that perfect CSI is available at the destination. In addition, when the number of relay is increased it is difficult to estimate CSI through all relays within coherence time of a channel because of the large amount of frame overhead for channel estimation. In a proposed channel estimation scheme, each terminal has distinct pilot signal which is orthogonal each other. By using orthogonal property of pilot signals, CSI is estimated over two pilot signal transmission phases so that frame overhead is reduced significantly. Due to the orthogonal property among pilot signals, estimation error does not depend on the number of relays. Simulation result shows that the proposed channel estimation scheme provides accurate CSI at the destination.

• Journal of Communications and Networks
• /
• v.14 no.3
• /
• pp.237-242
• /
• 2012

One of the major problems for accurate channel estimation in power line communication systems is impulsive noise. Traditional channel estimation algorithms are based on the assumption of Gaussian noise, or the need to locate the positions of impulsive noise. The algorithms may lose optimality when impulsive noise exists in the channel, or if the location estimation of impulsive noise is inaccurate. In the present paper, an effective channel estimation algorithm based on a robust cost function is proposed to mitigate impulsive noise. The proposed method can provide a closed-form solution, and the application of robust estimation theory enables the proposed method to be free from localization of impulsive noise and thus can guarantee that the proposed method has better performance. Simulations verified the proposed algorithm.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.8 no.4
• /
• pp.13-18
• /
• 2012

In this paper, we propose a noise estimation method for noise reduction. It is based on block and pixel-based noise estimation. We assume that an input image is contaminated by the additive white Gaussian noise. Thus, we use an adaptive Gaussian filter and estimate the amount of noise. It computes the standard deviation of each block and estimation is performed on pixel-based operation. The proposed algorithm divides an input image into blocks. This method calculates the standard deviation of each block and finds the minimum standard deviation block. The block in flat region shows well noise and filtering effects. Blocks which have similar standard deviation are selected as test blocks. These pixels are filtered by adaptive Gaussian filtering. Then, the amount of noise is calculated by the standard deviation of the differences between noisy and filtered blocks. Experimental results show that our proposed estimation method has better results than those by existing estimation methods.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2006.05a
• /
• pp.1129-1134
• /
• 2006

Mass estimation was derived as functions of acceleration magnitude and primary frequency. The conventional method of mass estimation used frequency data directly in the frequency domain. The signals that can be obtained sensor contained noise as well as impact signal. Therefore, how well we can detect the frequency data in noise directly determines the quality of mass estimation. To find exact frequency data, we used time-frequency analysis. The time frequency method are expected to be more useful than the conventional frequency domain analyses for the mass estimation problem on a plate type structure. Also it has been concluded that the smoothed WVD can give more reliable means than the other methodologies for the mass estimation in a noisy environment.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.2
• /
• pp.733-741
• /
• 2018

Capacity estimation is indispensable to ensure the safety and reliability of lithium-ion batteries in electric vehicles (EVs). Therefore it's quite necessary to develop an effective on-board capacity estimation technique. Based on experiment, it's found constant current charge time (CCCT) and the capacity have a strong linear correlation when the capacity is more than 80% of its rated value, during which the battery is considered healthy. Thus this paper employs CCCT as the health indicator for on-board capacity estimation by means of relevance vector machine (RVM). As the ambient temperature (AT) dramatically influences the capacity fading, it is added to RVM input to improve the estimation accuracy. The estimations are compared with that via back-propagation neural network (BPNN). The experiments demonstrate that CCCT with AT is highly qualified for on-board capacity estimation of lithium-ion batteries via RVM as the results are more precise and reliable than that calculated by BPNN.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.7 no.3
• /
• pp.107-113
• /
• 2011

An OFDMA(Orthogonal Frequency Division Multiple Access) includes a MIMO(Multi-Input Multi-Output) scheme for improving spectral efficiency and data throughput. Recognizing that the performance of MIMO system is heavily dependent upon the accuracy of channel estimation, we propose a novel channel estimation for the MIMO scheme based on OFDMA. Conventional interpolation-based channel estimation suffers from poor estimation error at specific subcarriers. Proposed scheme makes use of a planar interpolation instead of linear interpolation for those subcarriers of bad accuracy. Simulation results show that the proposed scheme improves the performance of MIMO system by improving the accuracy in channel estimation especially for the adverse subcarrier positions. It is observed that the proposed scheme outperforms the conventional method by about 2dB in terms of both mean squared error and overall bit error rate with a reasonable computational complexity.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2001.05a
• /
• pp.280-287
• /
• 2001

The studies to estimate the surface spectral reflectance of an object have received widespread attention using the multi-spectral camera system. However, the multi-spectral camera system requires the additional color filter according to increment of the channel and system complexity is increased by multiple capture. Thus, this paper proposes an algorithm to reduce the estimation error of surface spectral reflectance with the conventional 3-band RGB camera. In the proposed method, adaptive principal components for each pixel are calculated by renewing the population of surface reflectances and the adaptive principal components can reduce estimation error of surface spectral reflectance of current pixel. To evacuate performance of the proposed estimation method, 3-band principal component analysis, 5-band wiener estimation method, and the proposed method are compared in the estimation experiment with the Macbeth ColorChecker. As a result, the proposed method showed a lower mean square ems between the estimated and the measured spectra compared to the conventional 3-band principal component analysis method and represented a similar or advanced estimation performance compared to the 5-band wiener method.

• Journal of the Korea Safety Management & Science
• /
• v.11 no.1
• /
• pp.87-91
• /
• 2009

본 논문은 상대적으로 새로운 기법인 Parzen Density Estimation과 Multi-class SVM을 이용한 지능형 고장 탐색과 진단 방법을 제안하고 있다. 본 연구에서는 롤링 베어링을 대상으로 고장을 탐색하고 진단하기 위한 방법을 제안하는데 Parzen Density Estimation과 Multi-class SVM은 고장 클래스를 잘 표현할 수 있다. Parzen Density Estimation은 새로운 패턴 데이터의 거절과 알려진 데이터 패턴의 밀도의 평가에 의해 새로운 패턴을 찾아낼 수 있고, Multi-class SVM 기반의 방법은 여러 클래스의 고장을 support vector로 표현하여 고장 패턴을 찾아낼 수 있다. 본 연구에서는 실제의 다중 클래스를 가지는 롤링 베어링의 고장 데이터를 사용하여 고장 패턴을 탐색하는 과정을 보여주는데, 커널함수의 적절한 파라미터의 선택에 의한 Multi-class SVM 기반의 방법이 multi-layer perceptron이나 Parzen Density Estimation 방법보다 우수함을 입증한다.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.11 no.4
• /
• pp.344-350
• /
• 2011

Higher integrated density in 3D ICs also brings the difficulties of routing, which can cause the routing failure or re-design from beginning. Hence, precise congestion estimation at the early physical design stage such as floorplan is beneficial to reduce the total design time cost. In this paper, an effective estimation method of routing congestion is proposed for 3D ICs at floorplan stage. This method uses synthesized virtual signal nets, power/ground network and clock network to achieve the estimation. During the synthesis, the TSV location is also under consideration. The experiments indicate that our proposed method had small difference with the estimation result got at the post-placement stage. Furthermore, the comparison of congestion maps obtained with our method and global router demonstrates that our estimation method is able to predict the congestion hot spots accurately.