• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.48.1-48.1
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• 2021

Gaussian process regression (GPR) is a powerful method used for model-independent analysis of cosmological observations. In GPR, it is important to decide an input mean function and hyperparameters that affect the reconstruction results. Depending on how the input mean function and hyperparameters are determined in the literature, I divide into four main applications for GPR and compare their results. In particular, a zero mean function is commonly used as an input mean function, which may be inappropriate for reconstructing cosmological observations such as the distance modulus. Using mock data based on Pantheon compilation of type Ia supernovae, I will point out the problem of using a zero input and suggest a new way to deal with the input mean function.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.26-29
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• 2002

Radial Basis Function (RBF) networks is known as efficient method in classification problems and function approximation. The basis function of RBF networks is usual adopted normal distribution like the Gaussian function. The output of the Gaussian function has the maximum at the center and decrease as increase the distance from the center. For learning of neural network, the method treating the limited area of input space is sometimes more useful than the method treating the whole of input space. The q-normal distribution is the set of probability density function include the Gaussian function. In this paper, we introduce the RBF networks with the basis function of q-normal distribution and actually approximate a function using the RBF networks.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.30-33
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• 2002

To obtain good performance of radial basis function (RBF) neural networks, it needs very careful consideration in design. The selection of several parameters such as the number of centers and widths of the radial basis functions must be considered carefully since they critically affect the network's performance. We propose a learning algorithm for growing of complexity of RBF neural networks which is adapted automatically according to the complexity of tasks. The algorithm generates a new basis function based on the errors of network, the percentage of decreasing rate of errors and the nearest distance from input data to the center of hidden unit. The RBF's center is located at the point where the maximum of absolute interference error occurs in the input space. The width is calculated based on the standard deviation of distance between the center and inputs data. The steepest descent method is also applied for adjusting the weights, centers, and widths. To demonstrate the performance of the proposed algorithm, general problem of function estimation is evaluated. The results obtained from the simulation show that the proposed algorithm for RBF neural networks yields good performance in terms of convergence and accuracy compared with those obtained by conventional multilayer feedforward networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4A
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• pp.291-300
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• 2002

In this paper, a way of constituting optimized S box and G function was suggested in the block cipher whose structure is similar to SEED, which is KOREA standard of 128-bit block cipher. S box can be formed with nonlinear function and an affine transform. Nonlinear function must be strong with differential attack and linear attack, and it consists of an inverse number over GF(2$\^$8/) which has neither a fixed point, whose input and output are the same except 0 and 1, nor an opposite flexed number, whose output is one's complement of the input. Affine transform can be constituted so that the input/output correlation can be the lowest and there can be no fixed point or opposite fixed point. G function undergoes diffusive linear transform with 4 S-box outputs using the matrix of 4$\times$4 over GF(2$\^$8/). G function can be constituted so that MDS(Maximum Distance Separable) code can be formed, SAC(Strict Avalanche Criterion) can be met, there can be no weak input, where a fried point, an opposite fried point, and output can be two's complement of input, and the construction of hardware can be made easy. The S box and G function suggested in this paper can be used as a constituent of the block cipher with high security, in that they are strong with differential attack and linear attack with no weak input and they are excellent at diffusion.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.49-55
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• 2020

Information theoretic learning (ITL) methods based on random symbols (RS) use a set of random symbols generated according to a target distribution and are designed nonparametrically to minimize the cost function of the Euclidian distance between the target distribution and the input distribution. One drawback of the learning method is that it can not utilize the input power statistics by employing a constant stepsize for updating the algorithm. In this paper, it is revealed that firstly, information potential input (IPI) plays a role of input in the cost function-derivative related with information potential output (IPO) and secondly, input itself does in the derivative related with information potential error (IPE). Based on these observations, it is proposed to normalize the step-size with the statistically varying power of the two different inputs, IPI and input itself. The proposed algorithm in an communication environment of impulsive noise and multipath fading shows that the performance of mean squared error (MSE) is lower by 4dB, and convergence speed is 2 times faster than the conventional methods without step-size normalization.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.5
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• pp.137-144
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• 2000

In this paper, a longitudinal control of the lead vehicle for a platoon in IVHS Regulation Layer is proposed. The backstepping method has been used for the controller design. This method has an advantage in that its stability need not be proven since the controller is designed based on the Lyapunov Function. The control object is that the lead vehicle tracks a reference velocity and maintains a safe distance between the inter-platoons while the followers are keeping the speed of the lead vehicle of a platoon. The coordinate of system is transformed to a new coordinate system for its convenience to design controller. The new coordinate system is composed of error and new error variable. The error is the difference between the safe distance and the actual distance of inter-platoons. A new error variable is the difference between the velocity of vehicle and the estimated state of a system operated by the virtual input. The Lyapunov function is obtained based on the variables of new coordinate system. In the computer simulation, several cases have been studied such as when the lead vehicle is tracking the optimal speed. or a lead vehicle of the following platoon tracks the velocity of the previous platoon while maintaining a safe distance. Also a nonlinear engine time constant case has been investigated. All the simulation results show that the designed controller satisfies the control object sufficiently.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.439-446
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• 2014

Quantile regression models with errors in variables have received a great deal of attention in the social and natural sciences. Some eorts have been devoted to develop eective estimation methods for such quantile regression models. In this paper we propose an orthogonal distance quantile regression model that eectively considers the errors on both input and response variables. The performance of the proposed method is evaluated through simulation studies.

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.121-124
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• 2001

This paper proposed resource allocation algorithm for the minimum switching activity of functional unit in high level synthesis process as like DSP which is circuit to give many functional unit. The resource allocation method after scheduling use the power function calculating average hamming distance and switching activity of the between two input. First of all, the switching activity is calculated by the input value after calculating the average hamming distance between operation. In this paper, the proposed method though high If level simulation find switching activity in circuit each functional unit exchange for binary sequence length and value bit are logic one value. To use the switching activity find the allocation with minimal power consumption, the proposed method visits all control steps one by one and determines the allocation with minimal power consumption at each control step. As the existing method, the execution time can be fast according to use the number of operator and max control step. And it is the reduction effect from 6% to 8%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12B
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• pp.1175-1182
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• 2010

In this paper, we implemented a digital circuit which is targeted on FPGA for estimating azimuth information and distance between aircraft and ground station. All functions for signal processing of TACAN were integrated into a FPGA. The proposed hardware consists of input interface, register file, decoder, signal generator and main controller block. The designed hardware includes a function to generating pulse pair group for azimuth information, a function to responding the interrogation of aircraft for estimating distance between aircraft and ground station, and a function to provide ID information of ground station. The proposed hardware was implemented with FPGA chipset of ALTERA and occupied with 7,071 logic elements.

• Environmental and Resource Economics Review
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• v.13 no.1
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• pp.33-47
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• 2004

Even though the price of extracted but unprocessed coal has been available in Korea, the use of it as scarcity index would be inappropriate because of price subsidy. Following Halvorsen and Smith(1984), Kim and Lee(2002) derived estimates of the shadow price of unextracted coal by estimating the restricted cost function and differentiating with respect to the quantity of coal extracted. In Korea, however, due to the limited data the capital prices have been computed inconsistently case by case without relying on the robust formula like the Christensen-Jorgenson methodology used in US, which could result in biased estimators of the restricted cost function. In the paper the shadow prices of the resources in situ are obtained by measuring an input distance function defined by Shephard (1970), which requires only the data on the quantities of inputs and output. Empirical results for the Korean coal mining industry show that these shadow prices as a coal scarcity have increased fast by approximately three times in comparisons with those obtained by Kim and Lee.