• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.225-231
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• 2013

In this study, we propose the design of optimized pRBFNNs-based night vision face recognition system using PCA algorithm. It is difficalt to obtain images using CCD camera due to low brightness under surround condition without lighting. The quality of the images distorted by low illuminance is improved by using night vision camera and histogram equalization. Ada-Boost algorithm also is used for the detection of face image between face and non-face image area. The dimension of the obtained image data is reduced to low dimension using PCA method. Also we introduce the pRBFNNs as recognition module. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned by using Fuzzy C-Means clustering. In the conclusion part of rules, the connection weights of pRBFNNs is represented as three kinds of polynomials such as linear, quadratic, and modified quadratic. The essential design parameters of the networks are optimized by means of Differential Evolution.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.473-478
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• 2013

In this paper, we develop the Heavy Rain Advisory Decision Model based on intelligent neuro-fuzzy algorithm RBFNNs by using KLAPS(Korea Local Analysis and Prediction System) Reanalysis data. the prediction ability of existing heavy rainfall forecasting systems is usually affected by the processing techniques of meteorological data. In this study, we introduce the heavy rain forecast method using the pre-processing techniques of meteorological data are in order to improve these drawbacks of conventional system. The pre-processing techniques of meteorological data are designed by using point conversion, cumulative precipitation generation, time series data processing and heavy rain warning extraction methods based on KLAPS data. Finally, the proposed system forecasts cumulative rainfall for six hours after future t(t=1,2,3) hours and offers information to determine heavy rain advisory. The essential parameters of the proposed model such as polynomial order, the number of rules, and fuzzification coefficient are optimized by means of Differential Evolution.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.19-26
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• 2005

Image interpolation in the wavelet domain usually takes advantage of the probabilistic models for the intrascale statistics and the interscale dependency. In this paper, we adopt the linear model for the absolute values of wavelet coefficients of interpolated image across scale to estimate the variances of extrapolated bands. The proposed algorithm uses randomly generated wavelet coefficients based on the estimated parameters for probabilistic model. Random number generation according to the estimated probabilistic model may induce the 'salt and pepper' noise in subbands. We reduce the noise power by Wiener filtering. We observe that the proposed method generates the histogram of the subband coefficients similar to the that of original image. Experimental results show that our method outperforms the previous wavelet-domain interpolation method as well as the conventional bicubic method.

• Journal of Biomedical Engineering Research
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• v.16 no.1
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• pp.95-100
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• 1995

In this study, we have evaluated the effect of amplitude and frequency perturbation of EGG signal for single vowels associated with laryngeal pathology. The normal EGG signal was properly characterized by an autoregressive model which has an optimal order of ninth using the parametric method. This can be analyzed by determining the transfer function. Perturbations in the fundamental pitch and in the peak amplitude of EGG signal measured with a four-electrode system using the modulation/demodulation techniques were investigated for the purpose of developing a decision criteria for the laryngeal function analysis. The abnormal EGG signal has nonperiodic and unstable characteristics. It can be discriminated by the calculation of opening and closing time of glottis using the EGG signal. In case of normal and abnormal subjects, m$\pm$0.5*sd was discriminating line for frequency perturbation and m$\pm$2*sd for normal amplitude perturbations, respectively. Also, The normal and abnormal cases of the subjects can be discriminated effectively using the pattern of attractor derived with Hilbert transform of EGG signal.

• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.269-278
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• 1998

This paper describes a development of efficient stress ECG signal analysis algorithm. The algorithm consists of wavelet adaptive filter(WAF), QRS detector and ST segment detector. The WAF consists of a wavelet transform and an adaptive filter. The wavelet transform decomposed the ECG signal into seven levels using wavelet function for each high frequency bank and low frequency bank. The adaptive filter used the signal of the seventh lowest frequency band among the wavelet transformed signals as primary input. For detection of QRS complex, we made summed signals that are composed of high frequency bands including frequency component of QRS complex and applied the adaptive threshold method changing the amplitude of threshold according to RR interval. For evaluation of the performance of the WAF, we used two baseline wandering elimination filters including a standard filter and a general adaptive filter. WAF showed a better performance than compared filters in the noise elimination characteristics and signal distortion. For evaluation of WAF showed a better performance than compared filters in the noise elimination characteristics and signal distortion. For evaluation of results of QRS complex detection, we compared our algorithm with existing algorithms using MIT/BIH database. Our algorithm using summed signals showed the accuracy of 99.67% and the higher performance of QRS detection than existing algorithms. Also, we used European ST-T database and patient data to evaluate measurement of the ST segment and could measure the ST segment adaptively according to change of heart rate.

• Science of Emotion and Sensibility
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• v.18 no.1
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• pp.15-26
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• 2015

In this paper, amplitude and phase difference patterns for theta and alpha bands of the Evoked Potential(EP) in relation to perform a task at visual stimulus were analyzed using the Empirical mode decomposition(EMD). The EMD is applied to decompose EP signals with task-related sub-frequency band signals. Intrinsic mode function was implied in Hilbert transform and instantaneous amplitude and phase differences of theta and alpha were derived from Hilbert transformed EP. In a task status, large amplitude for both bands was observed at P2, N2, and P3 points as well as maximum phase difference was observed at N1 and P2. We confirmed that both bands are associated with a task at visual stimulus, and less associated with fixation. The proposed method enhances the time and frequency resolution in comparison with band-pass filter method which observed different phase results according to conditions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.12
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• pp.3638-3644
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• 2009

A CMOS multi-channel low-voltage current mode filter circuit is designed. The designed current-mode filter is based on linear cascode current-mode integrator that is newly proposed in this paper. When it is compared with that of the typical current-mirror type current-mode integrator, the proposed linear cascode current-mode integrator achieves high current gain and unity gain frequency. The designed filter is composed with 5th Chebyshev function and converted to active version by signal flow graph method. We verified that the designed filter can be applied to three-channel basedband, bluetooth, DECT and WCDMA with 0.51MHz~7.03MHz frequency tuning range by Hspice simulation using 1.8V-$0.18{\mu}m$ CMOS technology.

• The Journal of Engineering Geology
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• v.21 no.1
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• pp.1-13
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• 2011

Joint roughness is one of the most important parameters in analysis of rock slope stability. Especially in probabilistic analysis, the random properties of joint roughness influence the probability of slope failure. Therefore, a large dataset on joint roughness is required for the probabilistic analysis but the traditional direct measurement of roughness in the field has some limitations. Terrestrial LiDAR has advantagess over traditional direct measurement in terms of cost and time. JRC (Joint Roughness Coefficient) was calculated from statistical parameters which are known from quantitative methods of converting the roughness of the material surface into JRC. The mean, standard deviation and distribution function of JRC were obtained, and we found that LiDAR is useful in obtaining large dataset for random variables.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.968-974
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• 2010

We assessed the feasibility of discrete wavelet transform (DWT) applied for the spectral processing to enhance the estimation performance quality of soil organic matters using visible-near infrared spectra and mapped their distribution via block Kriging model. Continuum-removal and $1^{st}$ derivative transform as well as Haar and Daubechies DWT were used to enhance spectral variation in terms of soil organic matter contents and those spectra were put into the PLSR (Partial Least Squares Regression) model. Estimation results using raw reflectance and transformed spectra showed similar quality with $R^2$ > 0.6 and RPD> 1.5. These values mean the approximation prediction on soil organic matter contents. The poor performance of estimation using DWT spectra might be caused by coarser approximation of DWT which not enough to express spectral variation based on soil organic matter contents. The distribution maps of soil organic matter were drawn via a spatial information model, Kriging. Organic contents of soil samples made Gaussian distribution centered at around 20 g $kg^{-1}$ and the values in the map were distributed with similar patterns. The estimated organic matter contents had similar distribution to the measured values even though some parts of estimated value map showed slightly higher. If the estimation quality is improved more, estimation model and mapping using spectroscopy may be applied in global soil mapping, soil classification, and remote sensing data analysis as a rapid and cost-effective method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1992.10a
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• pp.25-30
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• 1992

최근 전자계산기를 이용한 진동해석 방법이 눈부시게 발달하여, 일반 구조물 이나 기계 구조물 등의 동특성을 설계 단계에서 정도 높게 예측하는 것이 가능하게 되었다. 그러나 종래의 구조해석은 주어진 시스템의 동특성을 위한 것으로 얻어진 동특성으로부터 질량, 관성제원 및 스프링상수값 등의 설계상 수값을 규명하는 연구는 미미한 실정이다. 이것에 대한 해결방법으로 크게 해석적인 방법과 실험적인 방법으로의 접근이 있어 왔다. 해석적인 방법으로 유한요소해석에서 얻은 모드좌표를 물리좌표로 변환하는 방법으로 Guyan의 정축소와 같은 절점축소를 행하는 방법이 고찰되었다. 실험적인 방법으로 가 진실험에서 얻은 전달함수나 모드파라미터로부터 [M], [K] 행렬을 결정하는 연구가 있었지만 어떤것도 질량, 스프링상수 등의 설계상수를 완전히 규명하 지는 못하였다. 또한, 설계 단계에서 필요한 질량, 관성제원 또는 스프링상수 등의 최적한 값이나, 원하는 시스템특성을 얻을 수 있는 설계상수의 적정한 폭을 구하는 연구는 설계자의 경험과 반복된 시행착오에 의존하는 실정이다. 감도해석은 이러한 문제점을 개선하는 수단으로 설계변수에 대한 동특성의 변화율을 구하는 것이다. 감도해석을 수행하는 것은 어느 설계변수를 수정하 는 것이 주어진 동특성에 부합되는 지를 알려주고, 어느 것을 수정하는 것이 원하는 방향의 동특성변화에 가장 효과적인지를 알려주는 것이다. 따라서 감 도해석을 이용하여 설계의 최적화 프로그램을 만들수 있고, 이것은 설계자가 요구하는 동특성을 목적함수로 하여 주어진 구조물을 최적화하는 설계상수 값을 얻을 수 있게 한다. 본 논문에서는 강체모델의 동특성으로부터 모델의 설계 상수를 규명하고, 동특성의 개선을 위하여 설계변수의 변경량을 물리좌 표계에서 얻는것을 목적으로 한다. 강체 마운트계의 관성제원 및 마운트강성 의 규명을 위하여 임으로 주어진 설계상수를 모델데이타로 하여 관성제원과 스프링 강성을 구하였다. 관성제원의 규명은 주어진 모델의 관성값을 모르는 것으로 하여 임의의 초기 관성값으로 감도해석에 의해 주어진 계의 관성값 을 물리 좌표계에서 규명하였다. 마운트 강성의 규명도 관성제원의 규명과 같은 방법으로 임의의 강성값으로 감도해석을 하여 강성값을 규명하였다. 또 한 감도해석에 의한 동특성 변경은 특정한 고유진동 수의 변경이 필요할 때, 고유진동수의 이동을 위한 관성제원의 변경 및 마운트 강성변경값을 예측할 수 있다. 본 연구수행의 기본적인 흐름도는 Fig.1.1과 같다. 위와 같은 작업 으로 엔진 마운트와 같은 강체 모델의 시스템 규명을 행하는 경우에 유한요 소해석 및 가진 실험으로 얻은 고유진동수의 정보 또는 원하는 고유진동수 의 특성을 기본으로 실제 설계에서 사용이 가능하도록 물리 좌표계에서 관 성 제원 및 스프링상수를 구할 수 있을 것이다.