• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.4
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• pp.42-49
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• 1997

A conventional adaptive noise canceller (ANC) using LMS algorithm suffers from the misadjustment of adaptive filter weights due to the gradient-estimate noise by input speech signal at steady state. In this paper, an ANC is proposed which uses the combination of VSLMS (variable step size LMS) and SA (sign algorithm) to improve steady state performance and convergence rate. SA algorithm is applied in speech region to prevent the weights from perturbing by output speech of ANC and VSLMS algorithm is applied to improve convergence rate and channel tracking ability in silence region and adaptive transient region. In compute rsimulation, the performance of the proposed VSLMS-SA combination algorithm is much better than LMS algorithm and the algorithm, recently proposed by greenberg, with adaptation step-size parameter determine dby sum method in convergence rate, channel tracking and steady state performance.

• Journal of Digital Convergence
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• v.13 no.8
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• pp.295-300
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• 2015

In vocabulary recognition using an HMM model which models the prior distribution for the observation of a discrete probability distribution indicates the advantages of low computational complexity, but relatively low recognition rate. The Bayesian techniques to improve vocabulary recognition model, it is proposed using a convergence of two methods to improve recognition noise-canceling recognition. In this paper, using a convergence of the prior probability method and techniques of Bayesian posterior probability based on HMM remove noise and improves the recognition rate. The result of applying the proposed method, the recognition rate of 97.9% in vocabulary recognition, respectively.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.319-328
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• 1993

The actual convergence rate of Newton-Raphson iteration method at each step is studied under the regularity conditions for the limiting distribution: The convergence rate of it is accelerated with good starting values. Hence we can decide a number of iterations according to our purposes.

• Journal of the Korean Statistical Society
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• v.24 no.1
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• pp.91-109
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• 1995

The rate of convergence to a random variable S for an almost certainly convergent series $S_n = \sum^n_{j=1} X_j$ of independent random variables is studied in this paper. More specifically, when $S_n$ converges to S almost certainly, the tail series $T_n = \sum^{\infty}_{j=n} X_j$ is a well-defined sequence of random variable with $T_n \to 0$ a.c. Various sets of conditions are provided so that for a given numerical sequence $0 < b_n = o(1)$, the tail series strong law of large numbers $b^{-1}_n T_n \to 0$ a.c. holds. Moreover, these results are specialized to the case of the weighted i.i.d. random varialbes. Finally, example are provided and an open problem is posed.

• Bulletin of the Korean Mathematical Society
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• v.32 no.2
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• pp.297-302
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• 1995

In [1], Cramer introduced the first large deviation theorem at a probability symposium in 1938. Since 1938, there have been many developments in the large deviation theorems.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.311-316
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• 2017

High Efficiency Video Coding (HEVC) is the newest video coding standard for improvement in video data compression. This new standard provides a significant improvement in picture quality, especially for high-resolution videos. A quadtree-based structure is created for the encoding and decoding processes and the rate-distortion (RD) cost is calculated for all possible dimensions of coding units in the quadtree. To get the best combination of the block an optimization process is performed in the encoder, called rate distortion optimization (RDO). In this work we are proposing a novel approach to enhance the overall RDO process of HEVC encoder. The proposed algorithm is performed in two steps. In the first step, like HEVC, it performs general rate distortion optimization. The second step is an extra checking where a SSIM based cost is evaluated. Moreover, a fast SSIM (FSSIM) calculation technique is also proposed in this paper.

• East Asian Economic Review
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• v.25 no.4
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• pp.403-424
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• 2021

AdaBoost tweaks the sample weight for each training set used in the iterative process, however, it is demonstrated that it provides more correlated errors as the boosting iteration proceeds if models' accuracy is high enough. Therefore, in this study, we propose a novel way to improve the performance of the existing AdaBoost algorithm by employing heterogeneous models and a stochastic twist. By employing the heterogeneous ensemble, it ensures different models that have a different initial assumption about the data are used to improve on diversity. Also, by using a stochastic algorithm with a decaying convergence rate, the model is designed to balance out the trade-off between model prediction performance and model convergence. The result showed that the stochastic algorithm with decaying convergence rate's did have a improving effect and outperformed other existing boosting techniques.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.12
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• pp.1210-1218
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• 2011

GA (Genetic Algorithms) are efficient for searching for global optima but may have some problems such as premature convergence, convergence to local extremum and divergence. These phenomena are related to the evolutionary operators. As population diversity converges to low value, the search ability of a GA decreases and premature convergence or converging to local extremum may occur but population diversity converges to high value, then genetic algorithm may diverge. To guarantee that genetic algorithms converge to the global optima, the genetic operators should be chosen properly. In this paper, we analyze the effects of the selection operator, crossover operator, and mutation operator on convergence properties, and propose the sweeping method of mutation probability and elitist propagation rate to maintain the diversity of the GA's population for getting out of the premature convergence. Results of simulation studies verify the feasibility of using these sweeping operators to avoid premature convergence and convergence to local extrema.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.6
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• pp.307-312
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• 2021

This paper proposes an adaptive time-delayed control approach with the integral sliding-mode surface for the fast convergence rate of robot manipulators. Adaptive switching gain aims to guarantee the system stability in such a way as to suppress time-delayed estimation error in the proposed control approach. Moreover, it makes an effort to increase the convergence ability in reaching the phase. An integral sliding-mode surface is employed to achieve a fast convergence rate in the sliding phase. The stability of the proposed one is proved to be asymptotically stable in the Lyapunov stability. The efficiency of the proposed control approach is illustrated with a tutorial example in robot manipulator, which is compared to that of the existing control approach.

• Journal of Technology Innovation
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• v.22 no.2
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• pp.31-50
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• 2014

Recent efforts of government to improve economic performance and increase employment through industrial convergence are being promoted actively. However, unfortunately, we have little of quantitative study on the following questions; (1) what is the rate of industrial convergence progressed?, and (2) what is the rate of total effects of industrial convergence spreaded?, and (3) which is the No. 1 industry in the magnitude of inductive effect of industrial convergence? In this study, we have measured and analyzed quantitatively the following questions using patent citation; (1) how is industrial convergence progressed?, and (2) how much has industrial convergence a effect on all industry?, and (3) what is the rate of the inductive effect of industrial convergence? In doing so, decision about industrial convergence has been made using patent citation and the effect of industrial convergence is drawn from convergence I/O table which made by patent citation.