• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.1997-2015
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• 2011

In this paper, we propose the enhanced network-based mobility management protocol, called enhanced proxy mobile ipv6 (E-PMIPv6), which can provide mobile nodes (MNs) with a fast and efficient mobility service in PMIPv6 domain. The proposed scheme can provide a fast and efficient mobility service to MNs and also the strength of network scalability and stability to an access network by proposing the dynamic virtual hierarchical network architecture. In addition, the pre-authentication procedure for an MN, based on the information of neighbor mobile access gateway (MAG) list in the enhanced-policy server (E-PS), is proposed to support seamless handover by reducing MN's handover latency. Through performance evaluations of numerical analyses and simulations, we have confirmed and verified the superiority of the proposed scheme compared to the conventional proxy mobile ipv6 (PMIPv6).

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.2
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• pp.88-94
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• 2003

In this paper, we propose a hierarchical triangular mesh generation method based on the motion information and a fast rude convergence method. From the variance of Image difference we decide the region that subdivision is required and perform the adequate triangulation method that is possible to yield a successive hierarchical triangulation. For fast node convergence, in initial search, we use the refinement method that separate the backgroung and object region and maintain the mesh connection by using the bilinear interpolation. The simulation result demonstrate that proposed triangulation method have performance in PSNR than the conventional BMA or order mesh based method and refinement is appropriate for the case of the mesh size is small.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.11
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• pp.917-924
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• 2003

Recurrent neural networks have been successfully applied to communications channel equalization. Major disadvantages of gradient-based learning algorithms commonly employed to train recurrent neural networks are slow convergence rates and long training sequences required for satisfactory performance. In a high-speed communications system, fast convergence speed and short training symbols are essential. We propose decision feedback equalizers using a recurrent neural network trained with Kalman filtering algorithms. The main features of the proposed recurrent neural equalizers, utilizing extended Kalman filter (EKF) and unscented Kalman filter (UKF), are fast convergence rates and good performance using relatively short training symbols. Experimental results for two time-varying channels are presented to evaluate the performance of the proposed approaches over a conventional recurrent neural equalizer.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.691-694
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• 1991

In a discrete parameter estimation system, the standard least squares method shows slow convergence. On the other hand, the weighted least squares method has relatively fast convergence. However, if the input is not sufficiently rich, then gain matrix grows unboundedly. In order to solve these problems, this paper proposes a modified least squares algorithm which prevents gain matrix from growing unboundedly and has fast convergence.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.263-268
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• 2010

The premature convergence of genetic algorithms (GAs) is the most major factor of slow evolution of GAs. In this paper we propose a novel method to solve this problem through competition of multiple offspring of in dividuals. Unlike existing methods, each parents in our method generates multiple offspring and then generated multiple offspring compete each other, finally winner offspring become to real offspring. From this multiple offspring competition, our GA rarel falls into the premature convergence and easily gets out of the local optimum areas without negative effects. This makes our GA fast evolve to the global optimum. Experimental results with four function optimization problems showed that our method was superior to the original GA and had similar performances to the best ones of queen-bee GA with best parameters.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.9B
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• pp.1226-1235
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• 2001

The convergence analysis of the improved multiplication free adaptive digital filter (IMADF) with a fractionally-spaced equalizer (FSE) to remove the intersymbol interference (ISI) in fast data transmission is presented. The IMADF structure use the one-step predicted filter in the multiplication-free adaptive digital filter (MADF) structure using the DPCM and Sign algorithm. In the experimental results, the IMADF algorithm has reduced the computational complexity by use of only the addition operation without a multiplier. Also, under the condition of identical stationary-state error, it could obtain the stabled convergence characteristic that the IMADF algorithm is almost same as the sign algorithm, but is better than the MADF algorithm. Here, this algorithm has effective characteristics when the correlation of the input signal is highly.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.8
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• pp.74-83
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• 1997

In this paper, we propose a new fractal image decoding algorithm with fast convergence speed by using the data dependence and the improved initial image estimation. Conventional method for fractal image decoding requires high-degrdd computational complexity in decoding process, because of iterated contractive transformations applied to whole range blocks. On proposed method, Range of reconstruction imagte is divided into referenced range and data dependence region. And computational complexity is reduced by application of iterated contractive transformations for the referenced range only. Data dependence region can be decoded by one transformations when the referenced range is converged. In addition, more exact initial image is estimated by using bound () function in case of all, and an initial image more nearer to a fixed point is estimated by using range block division estimation. Consequently, the convergence speed of reconstruction iamge is improved with 40% reduction of computational complexity.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.2
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• pp.375-389
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• 2015

An improved boundary element method is presented for numerical analysis of hydrodynamic behavior of marine structures. A new algorithm for numerical solution of the finite depth free-surface Green function in three dimensions is developed based on multiple series representations. The whole range of the key parameter R/h is divided into four regions, within which different representation is used to achieve fast convergence. The well-known epsilon algorithm is also adopted to accelerate the convergence. The critical convergence criteria for each representation are investigated and provided. The proposed method is validated by several well-documented benchmark problems.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.45-48
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• 2005

In this paper, we propose a new fast running FIR filter structure that improves the convergence speed of adaptive signal processing and reduces the computational complexity. The proposed filter is applied to wavelet based adaptive algorithm. Actually we compared the performance of the proposed algorithm with other algorithm using computer simulation of adaptive noise canceler based on synthesis speech. As the result, We know the proposed algorithm is prefer than the existent algorithm.

• Proceedings of the Acoustical Society of Korea Conference
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• 1991.06a
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• pp.38-41
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• 1991

RLS algorithms are required for applications to adaptive line enhancers, adaptive equalizers for voiceband telephone and HF modems, and wide-badn digital spectrum mobile raio in which their convergence time and tracking speed are significant. The fast QR RLS algorithm satisfies above the requirements. Its computational complexity is linearly proportional to the tap number of a filter, N and its performance remains numerically stable. From the result of simumulation, the fast QR RLS algorithm represented Cioffi is better than gradient based algorithm in its initial performance when being applied to an adaptive line enhancer for cancelling noise.