• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.5
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• pp.848-852
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• 2001

The biomedical signals such as ECG, EMG, EEG, and etc are very Important information to diagnose patients The signal is hard to filter the noise because that is mixed with a lot of noise and biomedical signal has the properties of nonlinear and time-variance. So, we will filter under the measure environment for system or patient. But the general adaptive fillet has brought on the distortion of signal because the adaptive filter adjust the filter coefficient with the fixed order of filter, that filter has the unsuitable order in each other environment. So we propose the dynamic structure adaptive filter that is used for improving that disadvantage. In experiment, we obtain the optimal order of adaptive filter and have food results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.2
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• pp.184-191
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• 1993

Continuous-time integrated filters, implemented in MOS VLSI technology, have been receiving considerable attention. In this paper, a continuous-time fifth order elliptic low-pass MOSFET-C filter has been designed with a cutoff frequency 3,400Hz. First an active RC filter is designed using cascade method which each block can be tunable. And then the resistors of an active RC network are replaced by a linear resistor using NMOS depletion transistors operated in the triode region. This continuous-time MOSFET filter have simpler structure than switched-capacitor filter, so reduce the chip area. The designed MOSFET-C filter characteristics are simulated by PSPICE program.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.10
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• pp.2447-2453
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• 2013

The digital images are being degraded by noise in the process of acquisition, storage and transmission, Gaussian or impulse noise is the representative noise. Meanwhile, the image has lots of tendency to be degraded by complex noise, so various researches are being conducted for reducing these complex noise. In this paper, to remove complex noise, the algorithm processed by modified switching median filter and modified adaptive weighted filter according to the result after judging the kinds of noise is proposed. In the simulation result, excellent denoising capabilities. Furthermore, we compared proposed algorithm with existing methods for objective judgement, and PSNR(peak signal to noise ratio) is used by the criterion of judgement.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.267-275
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• 2013

EKF has been widely used for GPS/INS integration as standard method but EKF has one well-known drawback. if the errors are not within the bounded region, the filter may be divergent. The particle filter has the advantage of the nonlinear and non-gaussian system. This paper proposes a method for compensating the GPS position errors based on the particle filter and presents loosely-coupled GPS/INS integration using proposed algorithm. We used GPS position pattern with particle filter and added attitude kalman filter for improving attitude accuracy. To verify the performance, the proposed method is compared with high cost GPS as reference. In the experimental result, we verified that the accuracy and robust were well improved by the proposed method filter effectively and robustness than by original loosely-coupled integration when vehicle turns at corner.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.411-413
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• 2013

Image signal processing is applied in different areas due to diffusion of smart phone, computer, multimedia etc. However, image most is damaged by impulse noise, and the need of denoising technology for improvement of image quality is coming to the fore. The existing methods for denoising such as mean filter and median filter, but they represent poor denoising. Therefore, the removes impulse noise, this paper proposed the modified mean filter algorithm using standard deviation, and as a simulation result, the proposed method showed excellent denoising capabilities to the existing methods.

• The Transactions of the Korean Institute of Power Electronics
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• v.14 no.4
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• pp.261-267
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• 2009

Due to the measurement noise or system noise, the performance of photovoltaic power generation system can be degraded. If this noise is contained in the solar array voltage measurement signal, the correct operation of the maximum power point tracker can not be guaranteed. The application of the extended Kalman filter to the photovoltaic system can obtain enhanced states estimation result. The Kalman filter provides a recursive solution to optimally estimate from random noise signals. Additionally, as a consequence of Kalman filter, the unmeasurable state such as inductor current can be estimated without current sensor. The methods for system modeling and extended Kalman filter design are presented and the experimental results verify the validity of the proposed system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.2
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• pp.67-74
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• 2005

This paper concerns attitude controller design for a 3-staged launch vehicle which has movable nozzle TVC systems for all stages as its control systems. The PD-type control gains are determined by shaping the corresponding closed-loop natural frequencies for the purpose of guaranteeing the required stability margin. Bending filters are also designed to stabilize the bending modes by using parametric optimization method. The designed controllers are verified using six degree of freedom flight simulations in MATLAB.

• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.6
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• pp.75-80
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• 1983

When an image with spot noise is smoothed by smoothing filters, the noise is almost eliminated However, the image is blurred. The algorithm that reduces such an image blurring is proposed in this paper. In the algorithm, the difference between noisy image and median filtered noisy image is smoothed. As the re-smoothing method, the absolute value of the difference is median filtered and the sign of the difference is affixed on the result. It is shown that the proposed algorithm is quite effective for noise elimination and also for image blurring decrease at the same time. In this paper, the algorithm is compared with the other smoothing methods.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.11a
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• pp.192-195
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• 2008

A sensor fault detection method for small turbo shaft engine considering multiple trim conditions is proposed. This engine is used in a helicopter. Firstly, under multiple trim conditions, we derive the linearized models from a nonlinear model which includes engine, rotor and feedback control loop. As a fault detection method, we adopt the Kalman filter based method. To keep continuity of estimates between the changes of trim conditions, we reconfigure the initial values of state variables at trim changes. We detect the faults with two steps that when the first filter does not alarm the faults for some sensors, the second filter is runned for other sensor. Via some simulations we show that the proposed method works well under multiple trim conditions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2671-2676
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• 2009

Empirical mode decomposition (EMD) is new time-frequency analysis method to decompose the signal adaptively and efficiently. The key idea of EMD is to decompose the signal into a set of functions defined by the signal itself, named Intrinsic Mode Functions (IMFs), which preserve the inherent properties of the original signal. Since the decomposition is based on the local time scale of the signal, it is not only applicable to nonlinear and non-stationary processes but also useful in biomedical signals like electrocardiogram (ECG). Traditional low-pass filter uses fourier transform to analysis signal in frequency domain, but EMD is filtered to maintain signal properties in time domain. This paper performed signal decomposition and filtering for noisy ECGs using EMD method. The proposed method is presented and compared with traditional low-pass filter by two performance indices. Our results show effectiveness for enhancement of the noisy ECG waveforms.