• 한국항공우주학회지
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• 제50권8호
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• pp.531-540
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• 2022

본 논문에서는 IMM 필터 기반으로 장사정포의 탄종을 식별하고 탄착점을 신속하게 예측하는 알고리즘을 제시한다. 탄도궤적 방정식을 시스템 모델로 사용하고, 각각 다른 탄도계수 값을 갖는 3가지 모델을 IMM 필터에 적용한다. 가속도를 중력, 공기저항, 양력에 의한 3가지 성분으로 나누고 양력가속도를 새로운 상태변수로 추가하여 추정한다. 속도벡터와 양력가속도가 수직이라는 운동학 조건을 유사 측정값으로 추가한 측정방정식을 다룬다. IMM 필터를 통해 추정된 상태변수와 모드 확률이 가장 높은 모델의 탄도계수를 기반으로 탄착점을 예측한다. 탄착점 예측을 위해 일반적으로 사용되는 룽게-쿠타 수치적분 대신, 준해석적인 방법을 사용하여 적은 계산량으로 탄착점을 예측할 수 있음을 설명한다. 마지막으로 최소제곱법을 이용한 상태변수 초기화 방법에 대해 제안하고 성능을 확인하였다. 탄종식별, 탄착점 예측 및 초기화를 포함한 통합 알고리즘을 제시하고 시뮬레이션을 통해 제안한 방법의 타당성을 검증하였다.

• 전기전자학회논문지
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• 제24권2호
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• pp.570-578
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• 2020

본 논문에서는 적응 2차 볼테라 필터를 효율적으로 구현할 수 있는 새로운 방법을 제안한다. 연산량 감소를 위해 제안된 UCFD-SVF는 수렴 성능이 저하되는 단점이 있다. UCFD-SVF의 적응 필터 계수가 적응이 진행되면서 그 에너지가 급격하게 증가하지 않는다는 점을 이용하여 적응 필터 계수를 주기적으로 초기화는 방법을 제안하였다. 또한 일정한 수렴 성능을 보장하기 위해 가변적인 간격으로 적응 필터 계수를 초기화하는 방법을 제안하였고, 비정상 환경에서 우수한 수렴 특성을 가짐을 적응 시스템 확인 응용을 위한 컴퓨터 모의 실험을 통해 보였다.

• 대한조선학회논문집
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• 제44권4호
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• pp.398-407
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• 2007

A smoothed particle hydrodynamics (SPH) method is applied for simulating two-dimensional free-surface problems. The SPH method based on the Lagrangian formulation provides realistic flow motions with violent surface deformation, fragmentation and reunification. In this study, the effect of computational parameters in SPH simulation is explored through two-dimensional dam-breaking and sloshing problem. The parameters to be considered are the speed of sound, the frequency of density re-initialization, the number of particle and smoothing length. Through a series of numerical test. detailed information was obtained about how SPH solution can be more stabilized and improved by adjusting computational parameters. Finally, some numerical simulations for various fluid flow problem were carried out based on the parameters chosen through the sensitivity study.

• ETRI Journal
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• 제45권3호
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• pp.418-432
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• 2023

In this work, we proposed a low-complexity hybrid layered tabu-likelihood ascent search (LTLAS) algorithm for large multiple-input multiple-output (MIMO) system. The conventional layered tabu search (LTS) approach involves many partial reactive tabu searches (RTSs), and each RTS requires an initialization and searching phase. In the proposed algorithm, we restricted the upper limit of the number of RTS operations. Once RTS operations exceed the limit, RTS will be replaced by low-complexity likelihood ascent search (LAS) operations. The block-based detection approach is considered to maintain a higher signal-to-noise ratio (SNR) detection performance. An efficient precomputation technique is derived, which can suppress redundant computations. The simulation results show that the bit error rate (BER) performance of the proposed detection method is close to the conventional LTS method. The complexity analysis shows that the proposed method has significantly lower computational complexity than conventional methods. Also, the proposed method can reduce almost 50% of real operations to achieve a BER of 10^-3.

• ETRI Journal
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• 제31권5호
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• pp.585-592
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• 2009

This paper presents a method for decoding high minimal distance ($d_{min}$) short codes, termed Cortex codes. These codes are systematic block codes of rate 1/2 and can have higher$d_{min}$ than turbo codes. Despite this characteristic, these codes have been impossible to decode with good performance because, to reach high $d_{min}$, several encoding stages are connected through interleavers. This generates a large number of hidden variables and increases the complexity of the scheduling and initialization. However, the structure of the encoder is well suited for analog decoding. A proof-of-concept Cortex decoder for the (8, 4, 4) Hamming code is implemented in subthreshold 0.25-${\mu}m$ CMOS. It outperforms an equivalent LDPC-like decoder by 1 dB at BER=$10^{-5}$ and is 44 percent smaller and consumes 28 percent less energy per decoded bit.

• International journal of advanced smart convergence
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• 제6권4호
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• pp.73-79
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• 2017

The Convolutional Neural Network (CNN) has shown an excellent performance in computer vision task. Applications of CNN include image classification, object detection in images, autonomous driving, etc. This paper will evaluate the performance of CNN model with ReLU and SELU as activation function. The evaluation will be performed on four different choices of hyperparameter which are initialization method, network configuration, optimization technique, and regularization. We did experiment on each choice of hyperparameter and show how it influences the network convergence and test accuracy. In this experiment, we also discover performance improvement when using SELU as activation function over ReLU.

• 전기학회논문지
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• 제62권9호
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• pp.1270-1275
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• 2013

A lot of research about camera calibration and lens distortion for wide-angle lens has been made. Especially, calibration for fish-eye lens which has 180 degree FOV(field of view) or above is more tricky, so existing research employed a huge calibration pattern or even 3D pattern. And it is important that calibration parameters (such as distortion coefficients) are suitably initialized to get accurate calibration results. It can be achieved by using manufacturer information or lease-square method for relatively narrow FOV(135, 150 degree) lens. In this paper, without any previous manufacturer information, camera calibration and barrel undistortion for fish-eye lens with over 180 degree FOV are achieved by only using one calibration pattern image. We applied QR decomposition for initialization and Regularization for optimization. With the result of experiment, we verified that our algorithm can achieve camera calibration and image undistortion successfully.

• Smart Structures and Systems
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• 제5권5호
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• pp.507-515
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• 2009

The present work is an alternative methodology in order to balance a nonlinear highly flexible rotor by using neural networks. This procedure was developed aiming at improving the performance of classical balancing methods, which are developed in the context of linearity between acting forces and resulting displacements and are not well adapted to these situations. In this paper a fully experimental procedure using neural networks is implemented for dealing with the adaptive balancing of nonlinear rotors. The nonlinearity results from the large displacements measured due to the high flexibility of the foundation. A neural network based meta-model was developed to represent the system. The initialization of the learning procedure of the network is performed by using the influence coefficient method and the adaptive balancing strategy is prone to converge rapidly to a satisfactory solution. The methodology is tested successfully experimentally.

• 항공우주시스템공학회지
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• 제10권1호
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• pp.8-14
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• 2016

The optimal estimation of a bearing only target tracking problem be achieved through the solution of the Fokker-Planck equation and the Bayesian update. Recently, a nonlinear filtering algorithm using a direct quadrature method of moments in which the associated Fokker-Planck equation can be propagated efficiently and accurately was proposed. Although this approach has demonstrated its promising in the field of nonlinear filtering in several examples, the "degeneracy" phenomenon, similar to that which exists in a typical particle filter, occasionally appears because only the weights are updated in the modified Bayesian rule in this algorithm. Therefore, in this paper to enhance the performance, a more stable measurement update process based upon the update equation in the Extended Kalman filters and a more accurate initialization and re-sampling strategy for weight and abscissas are proposed. Simulations are used to show the effectiveness of the proposed filter and the obtained results are promising.

• 전자공학회논문지A
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• 제32A권12호
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• pp.229-240
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• 1995

This paper proposes a new weighted random pattern testing technique to detect path delay faults in combinational logic circuits. When computing the probability of signal transition at primitive logic elements of CUT(Circuit Under Test) by the primary input, the proposed technique uses the information on the structure of CUT for initialization vectors and vectors generated by pseudo random pattern generator for test vectors. We can sensitize many paths by allocating a weight value on signal lines considering the difference of the levels of logic elements. We show that the proposed technique outperforms existing testing method in terms of test length and fault coverage using ISCAS '85 benchmark circuits. We also show that the proposed testing technique generates more robust test vectors for the longest and near-longest paths.