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RISS 인기검색어
- 검색키워드
- 저자 : 유진우(Jinwoo Yoo) (검색결과 34 건)
- 무료
- 기관 내 무료
- 유료
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An Affine Projection Algorithm with Pseudo-Fractional Projection Order
JinWoo Yoo(유진우) 대한전기학회 2019 전기학회논문지 Vol.68 No.7
This paper proposes an affine projection algorithm (APA) that determines its projection order using a pseudo-fractional method. The pseudo-fractional method adjusts the projection order by comparing the averages of the accumulated squared errors. The method relaxes the constraint of the conventional APA that the projection order must be integral, and it includes both the integral projection order and the fractional projection order. Simulation results show that the proposed algorithm achieves a faster convergence rate and a smaller steady-state estimation error than the existing algorithms.
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Variable Step-Size P-norm-like Affine Projection Algorithm
JinWoo Yoo(유진우),Bum Yong Park(박범용),JaeWook Shin(신재욱) 대한전기학회 2020 전기학회논문지 Vol.69 No.2
This letter presents a p-norm-like affine projection algorithm (APPA) and its variable step-size algorithm to improve the performance in high probability impulsive noise. The APPA is derived by minimizing the p-norm-like of an error vector that causes reducing error vector, when impulsive noise occurs. Therefore, the proposed algorithm has low steady-state estimation error in impulsive noise environment. In addition, its step-size algorithm is proposed by minimizing the mean-square deviation of the APPA to improve the performance in terms of the convergence speed and steady-state errors. The proposed algorithm is tested in the channel identification scenario including high probability impulsive noise. Simulation results show that the proposed algorithm has faster convergence rate and lower channel estimation errors than the variable step-size affine projection sign algorithm in impulsive noise environment.
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A Novel Affine Projection Algorithm for Fast Convergence of Sparse System
JinWoo Yoo(유진우) 대한전기학회 2020 전기학회논문지 Vol.69 No.5
This paper proposes a novel affine projection algorithm (APA) based on L0-norm constraint for improving the convergence rate in a sparse system. The proposed APA guarantees a fast convergence rate owing to the effect of L0-norm constraint. Experimental results confirm that implementing the proposed APA enhances the performance of adaptive filter for sparse system identification.
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고출력 측정 잡음에 강인한 성능을 보장하는 인접 투사 알고리즘
유진우(JinWoo Yoo) 대한전기학회 2019 전기학회논문지 Vol.68 No.7
This paper proposes a new robust affine projection algorithm (APA) through a modified criterion that consists of the Euclidean norm of the sum of the difference between the present filter-coefficient vector and the previous filter-coefficient vectors. Since the iterative update equation of the proposed APA is obtained from the modified criterion, it has robustness against the high power of measurement noises. Experimental results demonstrate that the proposed APA accomplishes smaller steady-state errors than the previous algorithms.
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