• Journal of Korea Society of Industrial Information Systems
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• v.4 no.4
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• pp.88-93
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• 1999

Several Iterative methods are considered, Gram-Schmidt algerian for thin orthogonalization and Lanczos methodfor a few extreme eigenvalues. For these methods, a variants of method is derived for which only one synchronization point per on iteration is required; that is one global communication in a message passing distributed-memory machine per one iteration is required The variant is called restructured method, and restructured method has better parallel properties to the conventional method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.11a
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• pp.110-113
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• 2019

본 논문에서는 임베디드 시스템에서의 양자화 기계학습을 수행할 경우 발생하는 양자화 오차를 효과적으로 보상하기 위한 방법론을 제안한다. 경사 도함수(Gradient)를 사용하는 기계학습이나 비선형 신호처리 알고리즘에서 양자화 오차는 경사 도함수의 조기 소산(Early Vanishing Gradient)을 야기하여 전체적인 알고리즘의 성능 하락을 가져온다. 이를 보상하기 위하여 경사 도함수의 최대 성분에 대하여 직교하는 방향의 보상 탐색 벡터를 유도하여 양자화 오차로 인한 성능 하락을 보상하도록 한다. 또한, 기존의 고정 학습률 대신, 내부 순환(Inner Loop) 없는 비선형 최적화 알고리즘에 기반한 적응형 학습률 결정 알고리즘을 제안한다. 실험결과 제안한 방식의 알고리즘을 비선형 최적화 문제에 적용할 시 양자화 오차로 인한 성능 하락을 최소화시킬 수 있음을 확인하였다.

• Journal of Advanced Navigation Technology
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• v.5 no.2
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• pp.111-122
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• 2001

In this paper, we study the performance of eigencanceller which use a eigenvector and eigenvalue in order to update a weighter vector. Eigencanceller can suppress directional interferences and noise effectively while maintaining specified beam pattern constraints. The constraints and optimal weight vector of eigencanceller vary by using interference and noise or desired signal, interference signal and noise as array input signal. From the analysis results in the steady state, We show that weight vectors in each case are simplified the form of projection equation that belongs to desired subspace orthogonal to interference subspace and eigencanceller has the better performance than RLS method through mathematical analysis and simulation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.5
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• pp.694-704
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• 2001

In this work, We evaluate the performance of eigencanceller which can suppress directional interferences and noise effectively while maintaining specified beam pattern constraints. The constraints and optimal weight vector of eigencanceller vary by using interference and noise or desired signal, interference and noise as array input signal. From the analysis results in the steady state, We show that weight vectors in each case are simplified the form of projection equation that belongs to desired subspace orthogonal to interference subspace and eigencanceller has the better performance than DMI method through mathematical analysis and simulation.

• The Journal of the Acoustical Society of Korea
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• v.27 no.5
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• pp.221-228
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• 2008

To estimate array shape with reference sources in SONAR systems, nearfield signal modeling is required for the reference sources near a towed array. Array shape estimation method based on the nearfield signal modeling generally exploits the spatial covariance matrix of the received reference sources. Among those method, nearfield eigenvector method uses the eigenvector corresponding to the maximum eigenvalue as a steering vector of the reference source. In this paper, we propose a simplified subspace fitting method based on the nearfield signal modeling with spherical wave modeling. Furthermore, we analyze performance of the array shape estimation methods based on the nearfield signal modeling for various environments. The results of the numerical experiments indicate that the simplified subspace fitting method and the nearfield eigenvector method with single reference source shows almost similar performance. Furthermore, the simplified subspace fitting method with 2 reference sources consistently estimates the shape of the array regardless of the incident angle of the reference sources, whereas the nearfield eigenvector method cannot apply for the case of 2 reference sources.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.6C
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• pp.580-593
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• 2003

A joint design scheme has been proposed to optimize the source encoder and the modulation signal constellation based on the minimization of the end-to-end distortion including both the quantization error and channel distortion. The proposed scheme first optimizes the VQ codebook for a fixed modulation signal set, and then the modulation signals for the fixed VQ codebook. These two steps are iteratively repeated until they reach a local optimum solution. It has been shown that the performance of the proposed system can be enhanced by employing a new efficient mapping scheme between codevectors and modulation signals. Simulation results show that a jointly optimized system based on the proposed algorithms outperforms the conventional system based on a conventional QAM modulation signal set and the VQ codebook designed for a noiseless channel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4A
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• pp.360-370
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• 2010

In this paper, a distributed beamforming problem is considered in an amplify-and-forward (AF) wireless relay network consist of multiple source-destination pairs and relaying nodes. To exploit degree of freedom of the number of beamformers, in the first step, we proposed that the sources transmit their signals through orthogonal channels. During the second step, the relays transmit their received signals multiplied by complex weights to amplify and compensate for phase changes introduced by the backward channels through one common channel. The optimal beamforming vectors are obtained through minimization of the total relay transmit power while the signal-to-interference-plus-noise ratios (SINRs) at the destinations are above certain thresholds to meet a quality of services (QoSs) level. In the numerical example, it is shown that the proposed scheme needs less transmit power for moderate network data rates than other schemes, such as space division multiplexing or time-division multiplexing scheme.

• Journal of Industrial Convergence
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• v.20 no.3
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• pp.33-40
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• 2022

Recently, IoT-linked services have been used in various environments, and IoT and artificial intelligence technologies are being fused. However, since technologies that process IoT data stably are not fully supported, research is needed for this. In this paper, we propose a processing technique that can optimize IoT data after generating embedded vectors based on machine learning for IoT data. In the proposed technique, for processing efficiency, embedded vectorization is performed based on QR such as index of IoT data, collection location (binary values of X and Y axis coordinates), group index, type, and type. In addition, data generated by various IoT devices are integrated and managed so that load balancing can be performed in the IoT data collection process to asymmetrically link IoT data. The proposed technique processes IoT data to be orthogonalized based on hash so that IoT data can be asymmetrically grouped. In addition, interference between IoT data may be minimized because it is periodically generated and grouped according to IoT data types and characteristics. Future research plans to compare and evaluate proposed techniques in various environments that provide IoT services.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.1
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• pp.36-41
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• 2009

In general, accurate attitude information is essential to perform the mission. Two algorithms are well-known to determine the attitude through two or more vector observations. One is deterministic method such as TRIAD algorithm, the other is optimal method such as QUEST algorithm. This Paper suggests the idea to improve performance of the TRIAD algorithm and to determine the attitude by combination of different sensors. First, we change the attitude matrix to Euler angle instead of using orthogonalization method and also use covariance in place of variance, then apply an unbiased minimum variance formula for more accurate solutions. We also suggest the methodology to determine the attitude when more than two measurements are given. The performance of the Averaging TRIAD algorithm upon the combination of different sensors is analyzed by numerical simulation in terms of standard deviation and probability.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.195-196
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• 2008

ECG 기반의 부정맥 자동 분류에 관한 연구는 지난 수십 년간 다양한 방법으로 연구되어 왔다. 많은 연구들이 부정맥을 구별해 낼 수 있는 특징 벡터를 찾아내기 위해 연구하였으나, 피험자의 ECG 특징이 각기 다르기 때문에 부정맥으로 인한 차이와 개인 간 차이를 구별하기 어려웠다. 생체데이터는 그 특성상 서로 다른 특징을 갖고 있으며, 다양한 특징을 가진 사람들에게 적용하기 위한 범용성과 부정맥 검출의 정확성 사이에 교환적 관계를 갖게 된다. 특히 ECG 데이터의 경우 사람 식별 데이터로 사용하고자 하는 연구가 있을 정도로 개인 간 편차가 분명하다. wavelet 분석방법은 다양한 mother wavelet을 사용할 수 있다는 점을 큰 장점으로 가지고 있으며, wavelet parameterization 기법을 사용하여 임의의 직교 wavelet basis를 발생시킬 수 있다. 본 논문은 wavelet parameterization을 사용하여 개인 간의 ECG 파형의 차이를 상쇄시키고, 부정맥의 차이만을 부각시킴으로써 ECG 기반의 부정맥 자동 분류 성능을 높이고자 하는데 목적이 있다.