• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.331-334
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• 2003

In this paper, using B-splines as universial approximators, we have obtained a plant parametrization which permits the construction of an adaptive observer. The particular property of this parametrization is that the dynamic order of the filters in this design does not depend on the number of parameters in the plant parametrization. This appears to be a beneficial property especially because the number of such parameters tends to be very high for universial approximator based designs.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.1
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• pp.76-84
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• 2002

In this paper, it is studied to remove the baseline wander and to minimize the distortion of ST segment in the noise filtering of ECG. In general, the standard filter and adaptive filter are used to remove the baseline wander of the ECG. But the standard filter is limited because the frequency of the baseline signal is variable and the apative filter is difficult to select the reference signal in case of using the adaptive filter. So we proposed a new method of the structure without reference signal using neural networks. To be convinced of the performance of this method, we used ECG data of MIT-BIHs. and obtained the result of the high performance,(-53.3[dB]) than standard filter(-16.3[dB]) and adaptive filter (-44.9[dB]).

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.866-870
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• 1989

Direct application of adaptive algorithm to the actual I/O is not a good strategy. The importance of using a kind of filter for estimation or control is strongly recommended. Simple pre-filtering method and pseudo-plant method is introduced. And, the properties of each methods are compared by analysis and/or simulations. A guideline for the choice of filters are proposed.

• Proceedings of the KOSOMBE Conference
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• v.1993 no.05
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• pp.74-77
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• 1993

Estimation and removal of power line interference in the electrocardiogram using adaptive noise cancelling techniques is presented. The system identification concepts are used to design the noise cancelling filter and the prediction error method is used to adjust filter coefficients. Computer simulation were performed to compare this method with the Lekov's method.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1125-1128
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• 1998

A new architecture for high-speed implementation of adaptive decision-feedback equalizer (ADFE) applicable to wide-band digital wireless modems is described. Rather than using conventional two's complement arithmetic, a novel complex-valued filter structure is devised, which is based on redundant binary (RB) arithmetic. The proposed RB complex-valued filter reduces the critical path delay of ADFE, as well as leads to a more compact implementation than conventional methods. Also, the carry-propagation free (CPF) operation of the RB arithmetic enhances its speed. To demonstrate the proposed method, a prototype chip set is designed. They are designed to contain two complexvalued filter taps along with their coefficient updating circuits, and can be cascaded to implement loger filter taps for high bit-rate applications.

• Journal of the Korea Society of Computer and Information
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• v.19 no.2
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• pp.101-107
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• 2014

This study is proposed the novel PPG sensor device and the signal processing method to replace the acceleration sensor that is used to reject motion artifacts contained in photoplethysmography(PPG). The proposed method is to reject motion artifacts by an adaptive filter based on the estimated motion artifact by using a blue LED light. To evaluate the performance of the proposed method experimentally, We did design a novel sensor consisted of blue/red LEDs and photo-sensor and implemented, and then rejected the motion artifacts by using an adaptive filter and the implemented sensor. In the results of the experiments, it is shown that the proposed sensor device and signal processing can reconstruct the PPG signal despite the occurrence of motion artifacts, and also that the SNR was 4.5 times of moving average filter. According to the experimental results, the proposed method can be applied to design a low-cost device.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.45-50
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• 2019

When PPG signal is used in mobile healthcare devices, the accuracy of the measured heartbeat decreases from the influence by the movement of the user. The reason is that the frequency band of the noise overlaps the frequency band of the PPG signal. In order to remove these same noises, the methods using frequency analysis method or application of acceleration sensor have been investigated and showed excellent performance. However, in applying these methods to low-cost healthcare devices, it is difficult to apply these methods because of much processing time and sensor's cost. In order to solve these problems, this study proposed the filter design method using an adaptive notch filter and the fuzzy inference system to extract more accurate heart rate in real time and evaluated its performance. As results, it showed better results than the other methods. Based on the results, when applying the proposed method to design the mobile healthcare device, it is possible to measure the heartbeat more accurately in real time.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.1041-1044
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• 1988

This paper considers the design problem of adaptive filters based an the state-space models for linear discrete-time stationary stochastic signal processes. The adaptive state estimator consists of both the predictor and the sequential prediction error estimator. The discrete Chandrasakhar filter developed by author is employed as the predictor and the nonlinear least-squares estimator is used as the sequential prediction error estimator. Two models are presented for calculating the parameter sensitivity functions in the adaptive filter. One is the exact model called the linear innovations model and the other is the simplified model obtained by neglecting the sensitivities of the Chandrasekhar X and Y functions with respect to the unknown parameters in the exact model.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.345-351
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• 2004

This Paper describes a nonlinear adaptive noise filter using neural network for digital controller system. Back-Propagation Learning Algorithm based MLP (Multi Layer Perceptron)is used an adaptive filters. In this paper. it assume that the noise of primary input in the adaptive noise canceller is not the same characteristic as that of the reference input. Experimental reaults show that the neural network base noise canceller outperforms the linear noise canceller. Especially to make noise cancel close to realtime, Primary input is divided by unit and each divided part is processed for very short time than all the processed data are unified to whole data.

• Journal of Power Electronics
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• v.14 no.4
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• pp.764-777
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• 2014

This study analyzes the mathematical relationship between DC-link voltage and system parameters for shunt active power filters (APFs). Analysis and mathematical deduction are used to determine the required minimum DC-link voltage for APF. A novel adaptive DC-link voltage controller for the three-phase four-wire shunt APF is then proposed. In this controller, the DC-link voltage reference value will be maintained at the required minimum voltage level. Therefore, power consumption and switching loss will effectively decrease. The DC-link voltage can also adaptively yield different DC-link voltage levels based on different harmonic currents and grid voltage levels and thus avoid the effects of harmonic current and grid voltage fluctuation on compensation performance. Finally, representative simulation and experimental results in a three-phase four-wire center-split shunt APF are presented to verify the validity and effectiveness of the minimum DC-link voltage design and the proposed adaptive DC-link voltage controller.