• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.449-455
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• 2004

Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate interval regression models for crisp input-output data. The proposed method is based on quadratic loss SVM, which implements quadratic programming approach giving more diverse spread coefficients than a linear programming one. The proposed algorithm here is model-free method in the sense that we do not have to assume the underlying model function. Experimental result is then presented which indicate the performance of this algorithm.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.1-6
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• 2017

For the algorithm of cross-information potential with delta functions (CIPD) which has superior performance in impulsive noise environments, a new method of employing the information of power variations of magnitude controlled input (MCI) in the weight update equation of the CIPD is proposed in this paper where the input of CIPD is modified by the Gaussian kernel of error. To prove its effectiveness compared to the conventionalCIPD algorithm, the distance between the current weight vector and its previous one is analyzed and compared under impulsive noise. In the simulation results the proposed method shows a two-fold improvement in steady state stability, faster convergence speed by 1.8 times, and 2 dB - lower minimum MSE in the impulsive noise situation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1240-1255
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• 1996

This paper suggests power optimization technique in multi-level SCPC system as a method for efficient utilization of limited satellite power. The power optimization is realized by optimal assignment of satellite input carrier powers considering interference and noise generated in up-link and down-link. The Fletcher-Powell algorithm searching minimum(or maximum) point using gradient information is used to detemine the optimal input carrier powers. To apply Flectcher-Powell algorithm mathematical descriptions and their partial derivatives to interference and nose are presented. Because a target, which should be optimized, is satellite input carrier power, amplitude of each carrier group will be assumed to be an independent variable. The performance criterion for optimal power assignmentis classified into 4 categories with respect to CNR of destination receiver earth station to meet the requirement for various satellite link environment. Simulation results for two-level, four-level and six-level SCPC system are presented.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.29A no.4
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• pp.91-98
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• 1992

In this paper, a new heuristic algorithm for designing combinational circuits suitable for verification testing is presented. The design method consists of argument reduction, input partitioning, output partitioning, and logic minimization. A new heuristic algorithm for input partitioning and output partitioning is developed and applied to designing combinational circuits to demonstrate its effectiveness.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.3
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• pp.10-21
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• 1993

Bilinear models are attractive for adaptive filtering applications because they can approximate a large class of nonlinear systems adequately, and usually with considerable parsimony in the number of coefficients compared with Volterra models. But bilinear filters have stability problem because they involve nonlinear feedback. Adaptive algorithms for bilinear filters may be diverge and have poor convergence characteristics when input signal is large In this paper, necessary and sufficient condition for mean square stability of bilinear filters for given input signal statistics is briefly described, and the method obtaining the input bound to guarantee the stability of bilinear filters is presented. New RPEM algorithm, which does not diverge and has the superior convergence characteristics compared with the conventional RPEM algorithm when input signal is large, is derived by applying the time-varying Kalman filtering concept to the conventional RPEM algorithm.

• Nuclear Engineering and Technology
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• v.33 no.5
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• pp.483-497
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• 2001

In this work, a neuro-fuzzy inference system combined with the wavelet denoising, PCA (principal component analysis) and SPRT (sequential probability ratio test) methods is developed to detect the relevant sensor failure using other sensor signals. The wavelet denoising technique is applied to remove noise components in input signals into the neuro-fuzzy system The PCA is used to reduce the dimension of an input space without losing a significant amount of information. The PCA makes easy the selection of the input signals into the neuro-fuzzy system. Also, a lower dimensional input space usually reduces the time necessary to train a neuro-fuzzy system. The parameters of the neuro-fuzzy inference system which estimates the relevant sensor signal are optimized by a genetic algorithm and a least-squares algorithm. The residuals between the estimated signals and the measured signals are used to detect whether the sensors are failed or not. The SPRT is used in this failure detection algorithm. The proposed sensor-monitoring algorithm was verified through applications to the pressurizer water level and the hot-leg flowrate sensors in pressurized water reactors.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.109-110
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• 2015

Estimation of rebar quantity may be used as an index to evaluate the economic feasibility of structural designs. However, when using the software to estimate the rebar quantity, there may be some limitations such as data loss caused by human errors and estimation delays caused by increased input time, since the information on arrangement of rebar is inserted manually. To solve the problems of such quantity estimation software, it is necessary to develop a method on automatic input/output of structural design information for quantity estimation and an algorithm for accurate estimation of rebar quantity. The purpose of this study is to improve the existing rebar quantity estimation by connecting with the database on information related to rebar estimation and the algorithm for rebar estimation, in order to develop an algorithm to estimate an accurate, net rebar quantity. The study result can be used as basic data for development of software for efficient structural designs and automatic framework estimation of buildings.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.8
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• pp.992-997
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• 1988

A generalized coding algorithm for multiple inputs multiple-valued logic gate based on shadow-casting is proposed. Proposed algorithm can minimize the useless pixels in case the number of inputs is not 2N (N is a natural number). A detailed analysis of advantages of proposed algorithm is presented and its effectiveness is demonstrated in case of three input binary system using inputs of 8*8 data.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.452-452
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• 2000

This paper deals with a fault detection algorithm for linear descriptor systems via unknown input PI observer. An unknown input PI observer is presented and its realization conditions is proposed by using the rank condition of system matrices. From the characteristics of unknown input PI observer, the states of system with unknown inputs are estimated and the magnitude of failures are detected and isolated easily by using integrated output error under the step failures. Finally, a numerical example is given to verify the effectiveness of the proposed algorithm.

• 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.