• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.7
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• pp.1247-1253
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• 2008

A design method of a T-S fuzzy model based reduced order nonlinear unknown input observer(NUIO) is presented. The fuzzy NUIO is designed based on the parallel distributed compensation(PDC) concept. It consists of a number of the linear UIOs, each of which is designed for each local linear model in the T-S fuzzy model of a class of nonlinear systems. The fuzzy NUIO provides not only the state estimates insensitive to the unknown inputs, for example, disturbances and faults etc., but also the estimates of the unknown inputs. Therefore, It can be employed in the state feedback control and disturbance rejection control of a class of nonlinear systems with unknown disturbances. It also applied to the robust residual generation for the fault detection and isolation systems and to the design of fault tolerant control systems. As an example, the NUIO is applied to an inverted pendulum system to show the state and disturbance estimation performance and to illustrate the fuzzy reduced order NUIO design method.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.20 no.2
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• pp.137-150
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• 2016

In this paper we analyze an a posteriori error estimator based on flux recovery for lowest-order finite element discretizations of elliptic interface problems. The flux recovery considered here is based on averaging the discrete normal fluxes and/or tangential derivatives at midpoints of edges with weight factors adapted to discontinuous coefficients. It is shown that the error estimator based on this flux recovery is equivalent to the error estimator of Bernardi and $Verf{\ddot{u}}rth$ based on the standard edge residuals uniformly with respect to jumps of the coefficient between subdomains. Moreover, as a byproduct, we obtain slightly modified weight factors in the edge residual estimator which are expected to produce more accurate results.

• Food Science and Biotechnology
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• v.18 no.2
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• pp.379-383
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• 2009

For an accurate risk assessment of furan, a potential human carcinogen, levels must be determined in human blood plasma using a simple and robust assay. In this study, solid phase microextraction-gas chromatography/mass spectrometry (SPME-GC/MS) was used to analyze blood plasma levels of furan in 100 healthy individuals who consumed a normal diet. The subjects were 30 to 70 years of age and 51% were women. Ultimately, an analytical method was established for analyzing furan in human blood. The limit of quantification (LOQ) and furan recovery rate in blood were 1.0 ppb and 104%, respectively. Finally, furan was detected in 21 individuals (13 males, 8 females) with levels ranging up to 17.86 ppb (ng furan/g food).

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.5
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• pp.240-246
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• 2014

A fault detector was developed for heat exchangers of a hybrid heat pump (HP) for household. The proposed detector can be applied directly to raw operating data. It is to monitor a tracking error between a measured saturation temperature and its state observer. The observer was estimated from a state-space model simulating dynamics of a heat exchanger. The real hybrid HP was substituted with a dynamic simulator that implemented two-phased heat transfer and was validated by experimental data. And artificial fault data were generated using the simulator. Diagnosing the data showed the following. The residual calculated from the state observer error shows a relatively robust consistency with respect fouling level. The fault detector is practically useful because it detects a threshold fouling beyond which the performance starts to deteriorate significantly.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.960-966
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• 2011

In this paper, an $\mathfrak{H}$_/$\mathfrak{H}_{\infty}$ fault detection and isolation (FDI) observer design problem is investigated for discrete-time delayed systems. To that end, a bank consisting of the sensor's number of observers is introduced. Each residual should be sensitive to a certain partial group of faults, but robust against the disturbance as far as possible. We formulate this multiobjective FDI problem as $\mathfrak{H}$_/$\mathfrak{H}_{\infty}$ observers design problem. Sufficient design condition is expressed as iterative linear matrix inequalities. The fault is then detected and isolated by evaluating the residuals through an FDI decision logic. A computer simulation is provided for verification of the proposed technique.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.189-192
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• 2001

A new configuration of acoustic echo canceler with stepsize predictor and comparator is proposed in this paper. Conventional acoustic echo cancelers using ES(Exponential Step)algorithm has fast convergence speed, but very weak in interference of environment. The proposed stepsize predictor and comparator improve conventional acoustic echo canceler's defects. The Stepsize predictor generates a stepsize value using residual power of error signal. The stepsize comparator selects the stepsize value that is better performance in a acoustic echo canceler using a stepsize decision factor. The Simulation results show superiority of the proposed acoustic echo canceler in environment interference.

• Proceedings of the KSPS conference
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• 2005.11a
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• pp.147-150
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• 2005

The performance of speech recognition in car environment is severely degraded when there is music or news coming from a radio or a CD player. Since reference signals are available from the audio unit in the car, it is possible to remove them with an adaptive filter. In this paper, we present experimental results of speech recognition in car environment using the echo canceller. For this, we generate test speech signals by adding music or news to the car noisy speech from Aurora2 DB. The HTK-based continuous HMT system is constructed for a recognition system. In addition, the MMSE-STSA method is used to the output of the echo canceller to remove the residual noise more.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.3 s.96
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• pp.215-221
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• 1999

The object of the thermal error compensation system in machine tools is improving the accuracy of a machine tool through real time error compensation. The accuracy of the machine tool totally depends on the accuracy of thermal error model. A thermal error model can be obtained by appropriate combination of temperature variables. The proposed method for optimal variable selection in the thermal error model is based on correlation grouping and successive regression analysis. Collinearity matter is improved with the correlation grouping and the judgment function which minimizes residual mean square is used. The linear model is more robust against measurement noises than an engineering judgement model that includes the higher order terms of variables. The proposed method is more effective for the applications in real time error compensation because of the reduction in computational time, sufficient model accuracy, and the robustness.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1464-1480
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• 2019

Robust tracking of infrared (IR) pedestrian targets with various backgrounds, e.g. appearance changes, illumination variations, and background disturbances, is a great challenge in the infrared image processing field. In the paper, we address a new tracking method for IR pedestrian targets via multi-feature local sparse representation (SR), which consists of three important modules. In the first module, a multi-feature local SR model is constructed. Considering the characterization of infrared pedestrian targets, the gray and edge features are first extracted from all target templates, and then fused into the model learning process. In the second module, an effective tracker is proposed via the learned model. To improve the computational efficiency, a sliding window mechanism with multiple scales is first used to scan the current frame to sample the target candidates. Then, the candidates are recognized via sparse reconstruction residual analysis. In the third module, an adaptive dictionary update approach is designed to further improve the tracking performance. The results demonstrate that our method outperforms several classical methods for infrared pedestrian tracking.

• Journal of Korea Multimedia Society
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• v.3 no.3
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• pp.263-271
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• 2000

In this paper, an acoustic echo canceller(AEC) is implemented by ADSP-2181. This AEC uses a noise robust adaptive algorithm and a postprocessing method which attenuates residual echo using cross-correlation between estimated error signal and microphone input signal. We propose new postprocessing method that uses two thresholds to prevent signal distortion after postprocessing and to improve the performance of AEC without extra computational burden. Through experiments using a 16 bit fixed-point DSP board (ADSP-2181 EZ-KIT Lite board), it is shown that the noise robust adaptive algorithm performs well in the double-talk situations and the convergence speed is comparable to NLMS. Using the postprocessor, ERLE is improved about 20 dB. As a result, the AEC with a postprocessor shows better performance than conventional ones.