• Journal of Korea Multimedia Society
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• v.12 no.1
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• pp.26-30
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• 2009

We propose an adaptive Recursive Least Rank(RLR) L-filter which uses an L-estimator in order statistics and is based on rank estimate in robust statistics. The proposed RLR L-filter is a non-linear adaptive filter using non-linear adaptive algorithm and adapts itself to optimal filter in the sense of least dispersion measure of errors with non-homogeneous step size. Therefore the filter may be suitable for applications when the transmission channel is nonlinear channels such as Gaussian noise or impulsive noise, or when the signal is non-stationary such as image signal.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.1
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• pp.1-10
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• 2013

In JPEG2000, the Cohen-Daubechies-Feauveau (CDF) 9/7-tap wavelet filter is implemented using the conventional lifting scheme. On the other hand, this wavelet filter has two problems: the filter coefficients remain complex, and the conventional lifting scheme does not consider the image edges in the coding process. This paper proposes an effective lifting scheme to solve these problems. For this purpose, optimal 9/7-tap wavelet filters were designed in two steps. In the first step, the appropriate filter coefficients were selected. In the second step, a median operator was employed to consider the image edges. The experimental results with the median lifting scheme and the combination of filter optimization with the median lifting show that the proposed methods outperform the well-known CDF 9/7-tap wavelet filter of JPEG2000 on the edge-dominant images.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.11a
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• pp.188-190
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• 2012

Compressed Sensing (CS) has been developed for several years. Among many CS algorithms for image, the Block-based Compressed Sensing with Smoothed Projected Landweber (BCS-SPL) demonstrates its excellent performance in low-complexity and near-optimal reconstruction. Several noise filtering algorithms of image reconstruction have been introduced such as the Wiener or the median filters, etc. In general, each filter has its own advantages and disadvantages depending on specific coding scheme. In this paper, we show that reconstruction performance can be varied according to the choice of filter. When a sub-rate value is changed, different filter causes different effect as well. Concerning the sub-rate, an inner filter can be chosen to improve the reconstructed image quality.

• Journal of the Optical Society of Korea
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• v.20 no.3
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• pp.368-380
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• 2016

There is no doubt that adaptive optics (AO) is the most promising method to compensate wavefront disturbance in free space optics communication (FSO). In order to improve the performance of the AO system described by discrete-time linear system model with time-delay and implicit phase turbulent model, new controllers based on a Kalman filter and its extensions are proposed. Based on the standard Kalman filter, we propose a fading memory filter to deal with the ruleless strong interference; sequential and U-D filters are applied to reduce implementation complexity for the embedded controllers. Theoretical analysis and the numerical simulations show that the proposed fading memory filter can upgrade the performance for AO systems in consideration of the unforeseen strong pulse interference, and the sequential and U-D filters perform well compared with a Kalman filter.

• Korean Journal of Materials Research
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• v.32 no.4
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• pp.223-229
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• 2022

A porous photocatalyst concrete filter was successfully produced to remove NOx, by mixing TiO₂ photocatalyst with lightweight aerated concrete. Ultra Fine Bubbles were used to form continuous pores inside the porous photocatalytic concrete filter, which was mixed via a bubble generation experiment. The optimal mixing condition was determined to be with 4 % of the bubble generation agent B. NO removal specimens were prepared for various photocatalytic loading conditions, and the specimen containing 3 % P-25 removed NO at a concentration of 1.03 µmol in 1 h. The NO removal rate of the porous photocatalytic concrete filter prepared in this study was 10.99 %. This photocatalytic filter performance was more than 9 times the amount of NO removed by a general photocatalytic filter. The porous photocatalyst concrete filter for removing NOx developed in this study can be applied to various construction sites and the air quality can be solved by reducing NOx contributing to the formation of fine particles.

• ALGAE
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• v.39 no.1
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• pp.51-56
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• 2024

The use of droplet digital polymerase chain reaction (ddPCR) has greatly improved the quantification of harmful protists, outperforming traditional methods like quantitative PCR. Notably, ddPCR provides enhanced consistency and reproducibility at it resists PCR inhibitors commonly found in environmental DNA samples. This study aimed to determine the most effective filter material for ddPCR protocols by assessing the reproducibility of species-specific gene copy numbers and filtration time across six filter types: cellulose acetate (CA), mixed cellulose ester (MCE), nylon (NY), polycarbonate (PC), polyethersulfone (PES), and polyvinylidene fluoride (PVDF). The study used two species of Chattonella marina complexes as a case study. Filtration rates were slower for NY, PC, and PVDF filters. Moreover, MCE, NY, PES, and PVDF yielded lower DNA amounts than other filters. Importantly, the CA filter exhibited the lowest variance (38-39%) and the highest determination coefficients (R² = 0.92-0.96), indicating superior performance. These findings suggest that the CA filter is the most suitable for ddPCR quantification of marine protists, offering quick filtration and reliable reproducibility.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.593-596
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• 2000

본 논문에서는 UMTS(Universal Mobile Telecommunications System)의 규격에 명시된 SRCF(Square Root Raised Cosine Filter) 와 호환성을 가지면서, 우수한 성능과 구현이 간단한 필터를 설계 및 구현하는 방법에 대하여 소개한다. 또한, VHDL을 이용하여 ALTERA FPGA서 필터를 직접 구현하는 결과를 보이고 있다.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.23 no.10
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• pp.820-825
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• 2010

In this study, we intended to design the optimal Fermi filter to apply the k-space date that is knee image of the rheumatoid arthritis patient acquired from the MRI (magnetic resonance imaging) instrument. After deciding the suitable coefficient for the Fermi filter, the results were compared with modified Fermi filter and inverse Chebyshev filter, Chebyshev filter, Elliptic filter and Butterworth filter. Firstly, in comparison to the results, the radiologist confirmed that modified Fermi filter was best decision for boundary of the rheumatoid arthritis images. The number of the black voxels of the histogram showed the quantity of the results. At the proposed filter images, numbers of the blacks voxels were statistically decreased. That meant voxels only appeared the black color were changed to others voxels color. Because the number of the total voxels was fixed, the area appeared block color could be effected to the other areas. If the modified Fermi filter were used for rheumatoid arthritis patient, the result will be better than other filters.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.2
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• pp.113-120
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• 1999

One of the important challenges facing control engineers in developing automated machineryis to be able to monitor the machines using remote sensors. Observrs are often used to reconstruct the machine variables of interest. However, conventional observers are unalbe to observe the machine variables when the machine models, upon which the observers are based, have inputs that cannot be measured. Since this is often the case, the authors previsously developed a steady-state optimal state and input observer for time-invariant systems [1], this paper extends that work to time-variant systems. A recursive observer, similar to a Kalman-Bucy filter, is developed . This optimal observer minimizes the trace of the error variance for discrete , linear , time-variant, stochastic systems with unknown inputs.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2311-2313
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• 2000

In this paper, we consider $H^{\infty}$ optimal Kalman filter problems for linear weakly coupled stochastic systems. We introduce a decomposition for the systems of the Hamiltonian form, which plays an important role of exclusion of ill-condition by ${\varepsilon}$-effect and the parallel computation possibility. It is shown that the algebraic Riccati equation of the weakly coupled $H^{\infty}$ optimal Kalman filter problem is decoupled into completely independent reduced-order, well-defined, two suboptimal Kalman filters.