• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2C
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• pp.148-154
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• 2010

In this paper, we first review LDPC codes in general and a belief propagation algorithm that works in logarithm domain. LDPC codes, which is chosen 802.11n for wireless local access network(WLAN) standard are required a large number of computation due to large size of coded block and iteration. Therefore, we presented three kinds of low computational algorithm for LDPC codes. First, sequential decoding with partial group is proposed. It has same H/W complexity, and fewer number of iteration's are required at same performance in comparison with conventional decoder algorithm. Secondly, we have apply early stop algorithm. This method is reduced number of unnecessary iteration. Third, early detection method for reducing the computational complexity is proposed. Using a confidence criterion, some bit nodes and check node edges are detected early on during decoding. Through the simulation, we knew that the iteration number are reduced by half using subset algorithm and early stop algorithm is reduced more than one iteration and computational complexity of early detected method is about 30% offs in case of check node update, 94% offs in case of check node update compared to conventional scheme.

• Structural Engineering and Mechanics
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• v.34 no.6
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• pp.719-738
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• 2010

The aim of this paper concerns with the nonlinear analysis of cable-stayed bridges including the vibration effect of cable stays. Two models for the cable stay system are built up in the study. One is the OECS (one element cable system) model in which one single element per cable stay is used and the other is MECS (multi-elements cable system) model, where multi-elements per cable stay are used. A finite element computation procedure has been set up for the nonlinear analysis of such kind of structures. For shape finding of the cable-stayed bridge with MECS model, an efficient computation procedure is presented by using the two-loop iteration method (equilibrium iteration and shape iteration) with help of the catenary function method to discretize each single cable stay. After the convergent initial shape of the bridge is found, further analysis can then be performed. The structural behaviors of cable-stayed bridges influenced by the cable lateral motion will be examined here detailedly, such as the static deflection, the natural frequencies and modes, and the dynamic responses induced by seismic loading. The results show that the MECS model offers the real shape of cable stays in the initial shape, and all the natural frequencies and modes of the bridge including global modes and local modes. The global mode of the bridge consists of coupled girder, tower and cable stays motion and is a coupled mode, while the local mode exhibits only the motion of cable stays and is uncoupled with girder and tower. The OECS model can only offers global mode of tower and girder without any motion of cable stays, because each cable stay is represented by a single straight cable (or truss) element. In the nonlinear seismic analysis, only the MECS model can offer the lateral displacement response of cable stays and the axial force variation in cable stays. The responses of towers and girders of the bridge determined by both OECS- and MECS-models have no great difference.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.295-309
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• 2009

In this study, an iterative maximum a posteriori (MAP) approach using a Bayesian model of Markovrandom field (MRF) was proposed for despeckling images that contains speckle. Image process is assumed to combine the random fields associated with the observed intensity process and the image texture process respectively. The objective measure for determining the optimal restoration of this "double compound stochastic" image process is based on Bayes' theorem, and the MAP estimation employs the Point-Jacobian iteration to obtain the optimal solution. In the proposed algorithm, MRF is used to quantify the spatial interaction probabilistically, that is, to provide a type of prior information on the image texture and the neighbor window of any size is defined for contextual information on a local region. However, the window of a certain size would result in using wrong information for the estimation from adjacent regions with different characteristics at the pixels close to or on boundary. To overcome this problem, the new method is designed to use less information from more distant neighbors as the pixel is closer to boundary. It can reduce the possibility to involve the pixel values of adjacent region with different characteristics. The proximity to boundary is estimated using a non-uniformity measurement based on standard deviation of local region. The new scheme has been extensively evaluated using simulation data, and the experimental results show a considerable improvement in despeckling the images that contain speckle.

• The Pure and Applied Mathematics
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• v.11 no.4
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• pp.293-308
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• 2004

Let K be a nonempty convex subset of an arbitrary Banach space X and $T\;:\;K\;{\rightarrow}\;K$ be a uniformly continuous strictly hemi-contractive operator with bounded range. We prove that certain Ishikawa iteration scheme with errors both converges strongly to a unique fixed point of T and is almost T-stable on K. We also establish similar convergence and almost stability results for strictly hemi-contractive operator $T\;:\;K\;{\rightarrow}\;K$, where K is a nonempty convex subset of arbitrary uniformly smooth Banach space X. The convergence results presented in this paper extend, improve and unify the corresponding results in Chang [1], Chang, Cho, Lee & Kang [2], Chidume [3, 4, 5, 6, 7, 8], Chidume & Osilike [9, 10, 11, 12], Liu [19], Schu [25], Tan & Xu [26], Xu [28], Zhou [29], Zhou & Jia [30] and others.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.232-238
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• 2003

In this paper, we propose a spatially adaptive image restoration algorithm using local statistics. The local mean, variance, and maximum values are utilized to constrain the solution space, and these parameters are computed at each iteration step using partially restored image. A parameter defined by the user determines the degree of local smoothness imposed on the solution. The resulting iterative algorithm exhibits increased convergence speed when compared to the non-adaptive algorithm. In addition, a smooth solution with a controlled degree of smoothness is obtained. Experimental results demonstrate the capability of the proposed algorithm.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.39.1-39.1
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• 2021

The Local Volume Mapper(LVM) project in the fifth iteration of the Sloan Digital Sky Survey (SDSS-V) will produce large integral-field spectroscopic survey data to understand the physical conditions of the interstellar medium in the Milky Way, the Magellanic Clouds, and other local-volume galaxies. We are developing the LVM Instrument control software. The architecture design of the software follows a hierarchical structure in which the high-level software packages interact with the low-level and mid-level software and hardware components. We adopt the spiral software development model in which the software evolves by iteration of sequential processes, i.e., software requirement analysis, design, code generation, and testing. This spiral model ensures that even after being commissioned, the software can be revised according to new operational requirements. We designed the software by using the Unified Modeling Language, which can visualize functional interactions in structure diagrams. We plan to use the SDSS software framework CLU for the interaction between components, based on the RabbitMQ that implemented the Advanced Message Queuing Protocol (AMQP).

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1061-1069
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• 2000

In this paper, a new genetic algorithm is proposed for solving multimodal function optimization problems that are not easily solved by conventional genetic algorithm(GA)s. This algorithm finds one of local optima first and another optima at the next iteration. By repeating this process, we can locate all the local solutions instead of one local solution as in conventional GAs. To avoid converging to the same optimum again, we devise a new genetic operator, called a Mendel operator which simulates the Mendels genetic law. The proposed algorithm remembers the optima obtained so far, compels individuals to move away from them, and finds a new optimum.

• Bulletin of the Korean Mathematical Society
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• v.54 no.1
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• pp.199-214
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• 2017

We consider fixed-point iterations constructed by simple transforming from a quadratic matrix equation to equivalent fixed-point equations and assume that the iterations are well-defined at some solutions. In that case, we suggest real valued functions. These functions provide radii at the solution, which guarantee the local convergence and the uniqueness of the solutions. Moreover, these radii obtained by simple calculations of some constants. We get the constants by arbitrary matrix norm for coefficient matrices and solution. In numerical experiments, the examples show that the functions give suitable boundaries which guarantee the local convergence and the uniqueness of the solutions for the given equations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.8
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• pp.891-897
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• 1992

A local iterative Image restoration method Is Introduced that processes with varying iteration numbers according to the local statistics. In general almost of the Iterative method applies Its algorithm to the whole Image without considering the local pixel informations, which Is not so effective for the processing time. Usually the edges or details have an Important role In visual effect. So in this paper we process the edges or the details many times while In the flat region we just pass over or decrease iterations. This method shows good MSE (Mean Square Error) improvement, better subjective qualify and reduced processing time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1194-1200
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• 2006

In this paper, we propose an adaptive MAP (Maximum A Posteriori) high-resolution image reconstruction algorithm using local statistics. In order to preserve the edge information of an original high-resolution image, a visibility function defined by local statistics of the low-resolution image is incorporated into MAP estimation process, so that the local smoothness is adaptively controlled. The weighted non-quadratic convex functional is defined to obtain the optimal solution that is as close as possible to the original high-resolution image. An iterative algorithm is utilized for obtaining the solution, and the smoothing parameter is updated at each iteration step from the partially reconstructed high-resolution image is required. Experimental results demonstrate the capability of the proposed algorithm.