• Journal of Broadcast Engineering
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• v.20 no.2
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• pp.265-272
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• 2015

A new technology on video frame rate up-conversion (FRUC) is presented by combining the median filter and motion estimation (ME) with an occlusion detection (OD) method. First, ME is performed to have a motion vector. Then, the OD method is used to refine motion vector in the occlusion region. Since the wrong motion vector can be obtained with high possibility in the occluded area, a median filtering that less depends on the motion vector is applied to that area, and since the motion vector is continuous and robust in the non-occluded area, BDMC(Bi-Directional Motion Compensated interpolation) is applied to obtain interpolated image in that area. BDMC using the bi-directional motion vectors achieves good results when continuity and robustness of the motion vector is higher. Experimental results show that the proposed algorithm provides better performance than the conventional approach. The average gain of PSNR (Peak Signal to Noise Ratio) is approximately 0.16 dB in the test sequences compared with BDMC.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.113-117
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• 1997

In this paper we detected the thrombosis formation by spectral analysis and neural network. Using microphone and amplifier, we measured the sound from the mechanical valve which is attached to the pneumatic ventricular assist device. The sound was sampled by A/D converter and the periodogram is the main algorithm or obtaining spectrum. We made the valvular thrombosis models using pellethane and silicon and they are thrombosis model on the disk, around the sewing ring and fibrous tissue growth across the orifice of valve. The spectrum of normal and 5 kinds of thrombotic valve were obtained and primary and secondary peak appeared in each spectrum waveform. So to distinguish the secondary peak of normal and thrombotic valve quantatively, 3 layer back propagation neural network.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.3
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• pp.140-145
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• 2001

The instantaneous voltage drop is occurred when the fault is happened on the nearby feeders. The instantaneous voltage drop is continued during relatively short period. But, the effect of it can be very severe to some sensitive devices. That is, it can be the reason of restart or malfunction of some devices. And these phenomenons can cause the enormous economical damage and shorten the lifetime of the devices. In this paper, the device which can compensate the instantaneous voltage drop, is studied. Through the computer simulation using PSCAD/EMTDC, the validity of the control algorithm using peak detection method is verified. And the Dynamic Voltage Restorer(DVR) prototype is designed and constructed. Through the experiment, the function and performance of the DVR prototype is verified.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.3
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• pp.587-594
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• 2010

In this paper, we propose an asynchronous IR-UWB ranging system based on the two-way ranging protocol. The periodic pulse sequence is used to measure a distance between two devices. At the receiver, a received signal is first transformed into a frequency-domain signal using an analog correlator bank and digital signal processing is followed in the frequency-domain. This make it possible for the system to use an ADC with a conversion speed of pulse rate. The proposed algorithm at the receiver side includes a peak detection procedure using mutipath channel compensation and matched filtering, and retransmits a pulse sequence synchronized with the detected peak. The validity of the proposed algorithm is verified from simulation results where the CM1 channel is assumed.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.559-568
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• 2017

Harmonic/inter-harmonic detection and analysis is an important issue in power system signal processing. This paper proposes a fast algorithm based on matching pursuit (MP) sparse signal decomposition, which can be employed to extract the harmonic or inter-harmonic components of a distorted electric voltage/current signal. In the MP iterations, the method extracts harmonic/inter-harmonic components in order according to the spectrum peak. The Fast Fourier Transform (FFT) and nonlinear optimization techniques are used in the decomposition to realize fast and accurate estimation of the parameters. First, the frequency estimation value corresponding to the maxim spectrum peak in the present residual is obtained, and the phase corresponding to this frequency is searched in discrete sinusoids dictionary. Then the frequency and phase estimations are taken as initial values of the unknown parameters for Nelder-Mead to acquire the optimized parameters. Finally, the duration time of the disturbance is determined by comparing the inner products, and the amplitude is achieved according to the matching expression of the harmonic or inter-harmonic. Simulations and actual signal tests are performed to illustrate the effectiveness and feasibility of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.2
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• pp.244-253
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• 2016

The QRS complex of ECG signal represents the depolarization and repolarization activities in the cells of ventricle. Accurate informations of $QRS_{onset}$ and $QRS_{offset}$ are needed for automatic analysis of ECG waves. In this study, using the amount of change in the QRS complex voltage values and the distance from the $R_{peak}$, we determined the junction point from Q-wave to R-wave and the junction point from R-wave to S-wave. In the next step, using the integral calculation based on the connection point, we detected $QRS_{onset}$ and $QRS_{offset}$. We use the PhysioNet QT database to evaluate the performances of the algorithm, and calculate the mean and standard deviation of the differences between onsets or offsets manually marked by cardiologists and those detected by the proposed algorithm. The experiment results show that standard deviations are under the tolerances accepted by expert physicians, and outperform the results obtained by the other algorithms.

• Journal of Biomedical Engineering Research
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• v.20 no.4
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• pp.451-459
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• 1999

During the electromyographic evaluation for the diagnosis of neuropathy, presence for site of lesion could be predicted by a detection of denervation potentials such as fibrillation potentials or positive sharp waves in a group of muscles. Unfortunately, since denervation potentials are distinguished by examiner's experience, it is possible to make mistake identifying endplate spikes as a denervation potential. The aim of the study was to extract parameters to make an algorithm for quantitative distinction between denervation potentials and endplate spikes. It will help to minimize the examiner's bias and to localize the site of lesion thus increase the reliability on EMG diagnosis. There types of signals, endplate spike, fibrillation potential and positive sharp wave were obtained from the EDB(extensor digitorum brevis) muscle using then neuropathic patients. Eight parameters such as duration, area, slope, peak-to-peak amplitude, positive peak negative peak amplitude, ratio of positive to negative peak amplitude, and number of phase were extracted and compared. As a results, peak-to-peak amplitude, positive peak amplitude, ratio of positive to negative peak amplitude showed statistically significant differences between endplate spikes and denervation potentials. It was concluded that those parameters could be used to establish an algorithm which will improve the accuracies in automated quantitative EMG diagnosis.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.762-766
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• 1998

Mechanical valve is one of the most widely used implantable artificial organs, Since its failure (mechanical failures and thrombosis to name two representative example) means the death of patient, its reliability is very important and early noninvasive detection is essential requirement . This paper will explain the method to detect the thrombosis formation by spectral analysis and neural network. In order quantitatively to distinguish peak of a normal valve from that of a thrombotic valve, a 3 layer backpropagation neural network, which contains 7,000 input nodes, 20 hidden layer and 1output , was employed. The trained neural network can distinguish normal and thrombotic valve with a probability that is higher than 90% . In conclusion, the acoustical spectrum analysis coupled with a neural network algorithm lent itself to the noninvasive monitoring of implanted mechanical valves. This method will be applied to be applied to the performance evaluation of other implantable rtificial organs.

• Journal of the Korea Society of Computer and Information
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• v.7 no.3
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• pp.49-55
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• 2002

This paper proposes speaker recognition algorithm which includes both the pitch parameter and the fuzzy. This study proposes a pitch detection method for the peak and valley pitch detection function by means of comparing spectra which utilizes the transform characteristics between time and frequency. It measures the similarity to the original spectrum while arbitrarily varying the period in the time domain. It heavily weights the error due to the changing characteristics of the phonemes, while it is strong against noise. In this paper, makes reference pattern using membership function and performs vocal track recognition of common character using fuzzy pattern matching in odor to include time variation width for non-linear utterance time.

• Journal of the Korea Society of Computer and Information
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• v.5 no.3
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• pp.51-57
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• 2000

This paper proposes speaker recognition algorithm which includes both the pitch and the fuzzy. This study proposes a pitch detection method for the peak and valley pitch detection function by means of comparing spectra which utilizes the transform characteristics between time and frequency. It measures the similarity to the original spectrum while arbitrarily varying the period in the time domain. It heavily weights the error due to the changing characteristics of the phonemes, while it is strong against noise. In this paper, makes reference pattern using membership function and performs vocal track recognition of common character using fuzzy pattern matching in order to include time variation width for non-linear utterance time.