• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.19-27
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• 1998

To achieve the required services in the next-generation cellular telephone systems, the size of the cell become smaller and/or is of mixed macrocells and microcells. For more efficient system control, We make use of the mobile position and velocity information, provided that the mobility information is relatively accurate. In this paper, we propose an improved version of path-loss measurement algorithm introduced in literature[11]. The microcellular structure with severe multipath fading, reflection and refraction make mobile position and velocity estimation very difficult. In the proposed method, the pre-recorded path-loss informations, called the discrete position data base, are searched to estimate the position. Velocity estimation is obtained as a difference of the position values with respect to the time difference. Moving average filter is applied to smooth the estimated velocity and to reduce the error in the estimates. We also propose a method to simplify system implementation by reducing search area for discrete area database.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1530-1537
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• 2007

In this paper, we implemented a speech emotion recognition system that can distinguish human emotional states from recorded speech captured by a single microphone and classify them into four categories: neutrality, happiness, sadness and anger. In general, a speech recorded with a microphone contains background noises due to the speaker environment and the microphone characteristic, which can result in serious system performance degradation. In order to minimize the effect of these noises and to improve the system performance, a MA(Moving Average) filter with a relatively simple structure and low computational complexity was adopted. Then a SFS(Sequential Forward Selection) feature optimization method was implemented to further improve and stabilize the system performance. For speech emotion classification, a SVM pattern classifier is used. The experimental results indicate the emotional classification performance around 65% in the computer simulation and 62% on the ARM platform.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.8A
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• pp.671-678
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• 2005

This paper proposed symbol rate method which does not require a priori knowledge on the symbol rate and simplified modulation identification method to classify BPSK, QPSK, 8PSK signal. In order to estimate the unknown symbol rate, sliding FFT and simple moving average to estimate the spectrum of the signals is utilized, and sliding window and decimation, LPF blcok to estimate the proper symbol rate is used. Although conventional modulation ID method must use SNR value as the test statistics, the receiver cannot estimate the SNR value since the receiver cannot know the modulation type at the start of communication, and bit resolution is high due to using nonlinear function such as log, cosh. Therefore, we proposed the simplified fixed SNR value method. The performance of symbol rate estimation and modulation ID is shown using Monte Carlo computer simulation. This paper show that symbol rate estimation also has good performance in low SNR, and proposed simplified fixed SNR method has almost equivalent performance compared to conventional method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4443-4449
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• 2011

ECG consists of various types of electrical signal on the heart, and feature point of these signals can be detected by analyzing the arrhythmia. So far, feature points extraction method for the detection of arrhythmia done in the many studies. However, it is not suitable for portable device using real time operation due to complicated operation. In this paper, R-peak were extracted using R-R interval and QRS width informations on patients. First, noise of low frequency bands eliminated using butterworth filter, and the R-peak was extracted by R-R interval moving average and QRS width moving average. In order to verify, it was experimented to compare the R-peak of data in MIT-BIH arrhythmia database and the R-peak of suggested algorithm. As a results, it showed an excellent detection for feature point of R-peak, even during the process of operation could be efficient way to confirm.

• Korean Journal of Agricultural Science
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• v.41 no.3
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• pp.169-175
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• 2014

Objective of this study was to investigate effects of pre-processing method and number of sampling leaves on stability of the reflectance measurement for Chinese cabbage and kale leaves. Chinese cabbage and kale were transplanted and cultivated in a plant factory. Leaf samples of the kale and cabbage were collected at 4 weeks after transplanting of the seedlings. Spectra data were collected with an UV/VIS/NIR spectrometer in the wavelength region from 190 to 1130 nm. All leaves (mature and young leaves) were measured on 9 and 12 points in the blade part in the upper area for kale and cabbage leaves, respectively. To reduce the spectral noise, the raw spectral data were preprocessed by different methods: i) moving average, ii) Savitzky-Golay filter, iii) local regression using weighted linear least squares and a $1^{st}$ degree polynomial model (lowess), iv) local regression using weighted linear least squares and a $2^{nd}$ degree polynomial model (loess), v) a robust version of 'lowess', vi) a robust version of 'loess', with 7, 11, 15 smoothing points. Effects of number of sampling leaves were investigated by reflectance difference (RD) and cross-correlation (CC) methods. Results indicated that the contribution of the spectral data collected at 4 sampling leaves were good for both of the crops for reflectance measurement that does not change stability of measurement much. Furthermore, moving average method with 11 smoothing points was believed to provide reliable pre-processed data for further analysis.

• The Journal of the Acoustical Society of Korea
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• v.25 no.6
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• pp.269-276
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• 2006

In this paper, we propose an emotion recognition system that can discriminate human emotional state into neutral or anger from the speech captured by a cellular-phone in real time. In general. the speech through the mobile network contains environment noise and network noise, thus it can causes serious System performance degradation due to the distortion in emotional features of the query speech. In order to minimize the effect of these noise and so improve the system performance, we adopt a simple MA (Moving Average) filter which has relatively simple structure and low computational complexity, to alleviate the distortion in the emotional feature vector. Then a SFS (Sequential Forward Selection) feature optimization method is implemented to further improve and stabilize the system performance. Two pattern recognition method such as k-NN and SVM is compared for emotional state classification. The experimental results indicate that the proposed method provides very stable and successful emotional classification performance such as 86.5%. so that it will be very useful in application areas such as customer call-center.

• ETRI Journal
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• v.37 no.1
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• pp.1-10
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• 2015

A blind hopping phase estimator is proposed for the demodulation of received signals in frequency-hopping spread spectrum systems. The received signals are assumed to be bandwidth limited with a shaping filter, modulated as frequency modulation (FM) or binary frequency shift keying (BFSK), and hopped by predetermined random frequency sequences. In the demodulation procedure in this paper, the hopping frequency tracking is accomplished by choosing a frequency component with maximum amplitude after taking a discrete Fourier transform, and the hopping phase estimator performs the conjugated product of two consecutive signals and moving-average filtering. The probability density function and Cramer-Rao low bound (CRLB) of the proposed estimator are evaluated. The proposed scheme not only is very simple to implement but also performs close to the CRLB in demodulating hopped FM/BFSK signals.

• Journal of Advanced Marine Engineering and Technology
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• v.21 no.5
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• pp.579-583
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• 1997

A diesel Engine rotates vibratively because of alternative explosion strokes. Traditional measurement of a diesel engine speed is carried out by measuring output voltage of FV convertor from input signals of MPU(magnetic pickup unit) or of DC tachometer. Because these measurement include also vibrative rotation of a diesel engine, an analog filter is often used to eliminate high frequency noises due to periodic explosion stroke. But by this method these high frequency noises do not eliminated effectively because noise frequencies are changed according to diesel engine speed. In this paper, author proposes a new measurement method of a diesel engine revolution which read digital signal directly from MPU and prove the utility of proposed method through the real experiment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.312-316
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• 2004

In this study, a spatial 3-dof haptic mechanism is implemented. The implemented mechanism does not employ the gear transmissions as velocity reducers for all three joints but uses wire-based transmissions, thereby it is able to minimize the frictions significantly. Also, by employing the structure of the four-bar mechanism to drive third joint from close to the base, the mechanism is able to minimize the inertia effect from the third actuator very effectively. Its kinematic analysis such as position and velocity analyses are performed first. Then, its operating software development, hardware implementation, and the related interfaces between a PC and the implemented Haptic device are completed. To evaluate its potential and its performance as a haptic device, a experiment generating a virtual constraint in a operational task space is conducted and preliminary results are discussed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1138-1141
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• 1995

An arc sensor for seam tracking is developed to automate sub-assembly welding in shipbuilding. We utilize a moving average method, which produces an effect of low-pass filter, to generate the position compensation. Therefore the sensor is able to modify the path of the weld seam in real time. By simplifying the compension process, the tunning time is reduced so that operators react quickly. It turns out that this sensor is highly reliable and it is installed and being used in SHI Keoje shipbuilding yard.