• 전기의세계
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• v.30 no.12
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• pp.822-831
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• 1981

Many different schemes of the adaptive observer and controller have been developed for both continuous and discrete systems. In this paper we have presented a new scheme of the reduced order adaptive observer for the single input discrete linear time invariant plant. The output equation of the plant, is transformed into the bilinear form in terms of system parameters and the states of the state variable filters. Using the plant output equation the discrete implicit adaptive observer based on the similar philosophy to Nuyan and Carroll is derived and the parameter adaptation algorithm is derived based on the exponentially weighted least square method. The adaptive model following control system is also constructed according to the proposed observer scheme. The proposed observer and controller are rather than simple structure and have a fast adaptive algorithm, so it may be expected that the scheme is suitable to the practical application of control system design. The effectiveness of the algorithm and structure is illustrated by the computer simulation of a third order system. The simulation results show that the convergence speed is proportinal to the increasing of weighting factor alpha, and that the full order and reduced order observer have similar convergence characteristics.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.08a
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• pp.225-230
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• 1998

In this paper, a Kalman filter approach for enhancing speech signals degraded by statistically independent additive nonstationary noise is developed. The autoregressive hidden markov model is used for modeling the statistical characteristics of both the clean speech signal and the nonstationary noise process. In this case, the speech enhancement comprises a weighted sum of conditional mean estimators for the composite states of the models for the speech and noise, where the weights equal to the posterior probabilities of the composite states, given the noisy speech. The conditional mean estimators use a smoothing spproach based on two Kalmean filters with Markovian switching coefficients, where one of the filters propagates in the forward-time direction with one frame. The proposed method is tested against the noisy speech signals degraded by Gaussian colored noise or nonstationary noise at various input signal-to-noise ratios. An app개ximate improvement of 4.7-5.2 dB is SNR is achieved at input SNR 10 and 15 dB. Also, in a comparison of conventional and the proposed methods, an improvement of the about 0.3 dB in SNR is obtained with our proposed method.

• Journal of electromagnetic engineering and science
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• v.7 no.4
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• pp.201-206
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• 2007

When the M-ary signal experiences the Rayleigh fading, the diversity schemes can reduce the effects of fading since the probability that all the signals components will fade simultaneously are reduced considerably. The symbol error probabilities for various M-ary signals, such as MDPSK, MPSK and MQAM, are mathematically derived for the SC-2(Selection Combining 2) demodulation system, whereby the two signals with the two largest amplitudes are coherently combined among the L branches. On the other hand, maximum ratio combining(MRC) requires the individual signals from each path to be time-aligned, cophased, optimally weighted by their own fading amplitude, and then summed. The propagation model used in this paper is the frequency-nonselective slow Rayleigh fading channel corrupted by the Additive White Gaussian Noise(AWGN). The numerical results presented in this paper are expected to provide information for the design of radio system using M-ary modulation method for above mentioned channel environment.

• Journal of Environmental Impact Assessment
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• v.18 no.1
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• pp.31-39
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• 2009

A lot of data which are used in environment analysis of air pollution have characteristics that are distributed continuously in space. In this point, the collected data value such as precipitation, temperature, altitude, pollution density, PM10 have spatial aspect. When geostatistical data analysis are needed, acquisition of the value in every point is the best way, however, it is impossible because of the costs and time. Therefore, it is necessary to estimate the unknown values at unsampled locations based on observations. In this study, spatial interpolation method such as local trend surface model, IDW(inverse distance weighted), RBF(radial basis function), Kriging were applied to PM10 annual average concentration of Seoul in 2005 and the accuracy was evaluated. For evaluation of interpolation accuracy, range of estimated value, RMSE, average error were analyzed with observation data. The Kriging and RBF methods had the higher accuracy than others.

• International Journal of Reliability and Applications
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• v.15 no.1
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• pp.23-50
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• 2014

This paper deals with formulation of optimum multi-objective modified step-stress accelerated life test (ALT) plan for Burr type-XII distribution under type-I censoring. Since it is impractical to estimate only one objective parameter after conducting costly ALT tests; also, it is not desirable to assume instantaneous changes in stress levels because of limited capacity of test equipments and the presence of undesirable failure modes, therefore, an optimum multi-objective modified step-stress ALT plan has been designed. The optimal test plan consists in determining the optimum low stress level and optimal time at which stress starts linearly increasing from low stress by minimizing the weighted sum of the asymptotic variances of the maximum likelihood estimator of quantile lifetimes at design constant stress. The method developed has been illustrated using an example. Sensitivity analysis has been carried out. Comparative study has also been done to highlight the merits of the proposed model.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.654-656
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• 1998

This paper presents an optimal identification method of nonlinear and complex system that is based on fuzzy-neural network(FNN). The FNN used simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. And we use a HCM Algorithm to find initial parameters of membership function. And then to obtain optimal parameters, we use the genetic algorithm. Genetic algorithm is a random search algorithm which can find the global optimum without converging to local optimum. The parameters such as membership functions, learning rates and momentum coefficients are easily adjusted using the genetic algorithms. Also, the performance index with weighted value is introduced to achieve a meaningful balance between approximation and generalization abilities of the model. To evaluate the performance of the FNN, we use the time series data for 9as furnace and the sewage treatment process.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.34 no.7
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• pp.257-266
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• 1985

A new method for the artificial beta cell which can be used to control the hyperglycemia in diabetic patients was represented. The relationship between the insulin infusion rate and the blood glucose concentration was described by the second order ARMA model, and the time varying parameters were identified by exponentially weighted least squares estimator. The design of controller was based on the pole assignment self tuning altorithm with discrete blood sampling and the constraints of input and output responsse rate were considered. The results of animal experiments show that this method may be a fruitful approach for regulating the blood glucose level. We expect that this device can be used as both therapeutic and research tools providing that its stability and reliability are improved a little more.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.4
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• pp.571-578
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• 1998

In this paper, we deal with a node weighted Steiner Ring Problem (SRP) arising from the deployment of Synchronous Optical Networks (SONET), a standard of transmission using optical fiber technology. The problem is to find a minimum weight cycle (ring) covering a subset of nodes in the network considering node and link weights. We have developed two mathematical models, one of which is stronger than the other in terms of LP bounds, whereas the number of constraints of the weaker one is polynomially bounded. In order to solve the problem optimally, we have developed some preprocessing rules and valid inequalities. We have also prescribed an effective heuristic procedure for providing tight upper bounds. Computational results show that the stronger model is better in terms of computation time, and valid inequalities and preprocessing rules are effective for solving the problem optimally.

• Journal of Sensor Science and Technology
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• v.25 no.6
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• pp.418-422
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• 2016

A filtering algorithm based on the decentralized moving average Kalman filter with uncertainties is proposed in this paper. The proposed filtering algorithm presented combines the Kalman filter with the moving average strategy. A decentralized fusion algorithm with the weighted sum structure is applied to the local moving average Kalman filters (LMAKFs) of different window lengths. The proposed algorithm has a parallel structure and allows parallel processing of observations. Hence, it is more reliable than the centralized algorithm when some sensors become faulty. Moreover, the choice of the moving average strategy makes the proposed algorithm robust against linear discrete-time dynamic model uncertainties. The derivation of the error cross-covariances between the LMAKFs is the key idea of studied. The application of the proposed decentralized fusion filter to dynamic systems within a multisensor environment demonstrates its high accuracy and computational efficiency.

• Journal of the Korean Society of Combustion
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• v.6 no.1
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• pp.36-43
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• 2001

The NOx emission characteristics of jet flames fueled with $H_2\;and\;CH_4$ were studied. Experimental and numerical investigations were carried out for various flames with varying equivalence ratio, fuel flow rate and nozzle diameter. The Emission indices of NOx(EINOx) were measured by chemiluminescent method and calculated by numerical model based on detailed chemistry. The results show that EINOx of $CH_4\;and\;H_2$ flames have different trends in terms of equivalence ratio and fuel flow rate but have the same trends in terms of nozzle diameter. These differences can be explained by the following Thermal and Prompt trends in both flames. Thermal EINOx is quite sensitive to the residence time in the high-temperature region weighted by the maximum flame temperature. Prompt EINOx is mainly influenced by flame surface area of each combustion conditions.