• Journal of Wetlands Research
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• v.11 no.2
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• pp.89-98
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• 2009

This study determines the stream mean slope, stream slope and longitudinal stream profile based on the concept of informational entropy. Maximizing the entropy will make the probability distribution of longitudinal stream profile as uniform as possible while satisfying the constraints. Using this relationships the mean stream slope, stream slope and longitudinal stream profile formulas were derived. The parameters of the applied streams were estimated by the least square method using the geomorphological factors of Dalchon stream basin obtained from Chungcheong Buk-Do local stream consolidation scheme drawings. The comparative investigation was performed between the observed and simulated mean stream slope and longitudinal stream profile, and are in good agreement with the measured data. It is noted that this results can be used in the estimation of stream mean slope and longitudinal stream profile.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.4
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• pp.11-22
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• 1999

Least-mean-square(LMS) adaptive filters have proven to be extremely useful in a number of signal processing tasks. However LMS adaptive filter suffer from a slow rate of convergence for a given steady-state mean square error as compared to the behavior of recursive least squares adaptive filter. In this paper an efficient signal interference control technique is introduced to improve the convergence speed of LMS algorithm with tap weighted vectors updating which were controled by reusing data which was abandoned data in the Adaptive transversal filter in the scheme with data recycling buffers. The computer simulation show that the character of convergence and the value of MSE of proposed algorithm are faster and lower than the existing LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity of computation. Adaptive transversal filter with proposed data recycling buffer algorithm could efficiently reject ISI of channel and increase speed of convergence in avoidance burden of computational complexity in reality when it was experimented having the same condition of LMS algorithm.

• Journal of Korea Multimedia Society
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• v.9 no.8
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• pp.1000-1009
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• 2006

We propose an adaptive linear interpolation locating sub-pixels. We utilize a pixel-based parameter in the conventional linear interpolation. To optimally obtain the parameter, we propose a generic interpolation structure including a low pass filter and minimum mean square error. We also propose a simple version of the generic interpolation method, which obtain a closed-form solution. Simulation results show that the proposed method is superior to the state-of-the-art methods such as warped distance linear interpolation and shifted linear interpolation, as well as the conventional method such as the linear interpolation and the cubic convolution interpolation in terms of the subjective and objective image quality.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.5
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• pp.459-464
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• 2016

The mobile communication service is widely used and the repeaters is rapidly increasing because of the extending service areas. we propose a new Signed CMA(: Constant Modulus Algorithm) algorithm for ICS(: Interference Cancellation System) as a larger service area of mobile communication service. The proposed Signed CMA algorithm improved performances by adjusting step size values. We showed that the proposed algorithm could improve the Mean Square Error(: MSE) performance of Signed CMA. MATLAB(: Matrix Laboratory) is employed to analyze the proposed algorithm and to compare it with the experimental results. At the convergence of 1000 iteration state, the MSE(: Mean Square Error) performance of the proposed Signed CMA algorithm with step size of 0.0065 is about 5 dB better than the conventional CMA algorithm.

• Journal of Korean Society of Transportation
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• v.18 no.4
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• pp.117-126
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• 2000

Conventional methods for collecting origin-destination trips have been mainly relied on the surveys of home or roadside interview. However, the methods tend to be costly, labor intensive and time disruptive to the trip makers, thus the methods are not considered suitable for Planning applications such as routing guidance, arterial management and information Provision, as the parts of deployments in Intelligent Transport Systems Motivated by the problems, more economic ways to estimate origin-destination trip tables have been studied since the late 1970s. Some of them, which have been estimating O-D table from link traffic counts are generally Entropy maximizing, Maximum likelihood, Generalized least squares(GLS), and Bayesian inference estimation etc. In the Paper, with user equilibrium constraint we formulate GLS problem for estimating O-D trips and develop a solution a1gorithm by using Genetic Algorithm, which has been known as a g1oba1 searching technique. For the purpose of evaluating the method, we apply it to Seoul inner ringroad and compare it with gradient method proposed by Spiess(1990). From the resu1ts we fond that the method developed in the Paper is superior to other.

• Journal of the Korean Institute of Gas
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• v.16 no.1
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• pp.26-32
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• 2012

The autoignition temperature is one of the most important physical properties used to determine the flammability characteristics of chemical substances. Despite the needs of the experimental autoignition temperature data for the design of chemical plants, it is not easy to get the data. This study have built and compared partial least squares (PLS) and support vector machine (SVM) models to predict the autoignition temperatures of 503 organic compounds out of DIPPR 801. As the independent variables of the models, 59 functional groups were chosen based on the group contribution method. The prediction errors calculated from cross-validation were employed to determine the optimal parameters of two models. And, particle swarm optimization was used to get three parameters of SVM model. The PLS and SVM results of the average absolute errors for the whole data range from 58.59K and 29.11K, respectively, indicating that the predictive ability of the SVM is much superior than PLS.

• The Journal of the Acoustical Society of Korea
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• v.13 no.3
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• pp.16-24
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• 1994

A single channel adaptive noise canceling (ANC) technique is presented for removing effects of additive noise on the speech signal. The conventional method obtains a reference signal using the pitch estimated on a frame basis from the input speech. The proposed method, however, gets the reference signal using the delay estimated recursively on a sample by sample basis. To estimate the delay, we derive recursion formula of autocorrelation function and average magnitude difference function. The performance of the proposed method is evaluated for the speech signals distorted by the additive white Gaussian noise. Experimental results with normalized least mean square (NLMS) adaptive algorithm demonstrate that the proposed method improves the perceived speech quality quite well besides the signal-to-noise ratio.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.7
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• pp.1321-1327
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• 2009

In this paper, as the mobile communication service is widely used and the demand for wireless repeaters is rapidly increasing because of the easiness of extending service areas. But a wireless repeater has a problem the oscillation due to feedback signal. We proposed a new hybrid interference canceller using the adaptive filter with CMA(Constant Modulus Algorithm)-Grouped LMS(Least Mean Square) algorithm in the adaptive interference canceller. The proposed interference canceller has better channel adaptive performance and a lower MSE(Mean Square Error) than conventional structure because it uses the cancellation method of Grouped LMS algorithm. The proposed detector uses the LMS algorithms with two different step size to reduce mean square error and to obtain fast convergence. This structure reduces the number of iterations for the same MSE performance and hardware complexity compared to conventional nonlinear interference canceller.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.1
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• pp.27-35
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• 2005

Ultrasonic inspection methods are widely used for detecting flaws in materials. The signal analysis step plays a crucial part in the data interpretation process. A number of signal processing methods have been proposed to classify ultrasonic flaw signals. One of the more popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature spare. This paper describes an alternative approach which uses the least mean square (LMS) method and exportation maximization (EM) algorithm with the model based deconvolution which is employed for classifying nondestructive evaluation (NDE) signals from steam generator tubes in a nuclear power plant. The signals due to cracks and deposits are not significantly different. These signals must be discriminated to prevent from happening a huge disaster such as contamination of water or explosion. A model based deconvolution has been described to facilitate comparison of classification results. The method uses the space alternating generalized expectation maximiBation (SAGE) algorithm ill conjunction with the Newton-Raphson method which uses the Hessian parameter resulting in fast convergence to estimate the time of flight and the distance between the tube wall and the ultrasonic sensor. Results using these schemes for the classification of ultrasonic signals from cracks and deposits within steam generator tubes are presented and showed a reasonable performances.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.1 no.1
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• pp.123-132
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• 2002

In this study, the static and dynamic characteristics of endmilling process was modelled and the analytic realization of chatter mechanism was discussed. In this regard, We have discussed on the comparative assessment of recursive time series modeling algorithms that can represent the machining process and detect the abnormal machining behaviors in precision endmilling operation. In this study, simulation and experimental work were performed to show the malfunctional behaviors. For this purpose, new recursive least square method (RLSM) were adopted for the on-line system identification and monitoring of a machining process, we can apply these new algorithms in real process for detection of abnormal chatter. Also, The stability lobe of chatter was analysed by varying parameter of cutting dynamices in regenerative chatter mechanics.