• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.173-184
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• 2004

A statistical software for nonlinear regression analysis, NLIN2000, is introduced. This software, operated tinder the Window systems, has many user-friendly functions and Provides various statistics. As an upgraded version of the Previous Program operated under the DOS system, NLIN2000 provides easier steps for model specification and fitting process than any other statistical packages. Also it has a database system for model functions which has addition and deletion options. While it can be a useful research tool for statisticians, NLIN2000 can be used practically also by researchers in many other scientific fields, who needs nonlinear regression analysis for their study.

• Proceedings of the Acoustical Society of Korea Conference
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• 1993.06a
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• pp.54-57
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• 1993

본 논문은 스피커 시스템의 이상적이지 못한 특성으로 인해 발생하는 비선형 왜곡을 분석하고 스피커에 입력하는 신호를 처리함으로써 비선형 왜곡을 감소시키도록 하는 것을 목적으로 한다. 비선형 왜곡의 가장 큰 요인인 강성과 force factor의 비선형성을 변위에 관한 2차함수로 모델링하여 이것을 바탕으로 전처리의 여러 계수를 결정하며 변위를 측정하여 귀환시키는 대신 선형 운동방정식을 적용하여 변위를 예측하도록 함으로써 시스템의 구현을 간단히 할 수 있도록 하였다. 이 왜곡보상시스템을 하드웨어로 설계하였다.

• Aerospace Engineering and Technology
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• v.8 no.2
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• pp.1-7
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• 2009

The Geostationary Ocean Color Imager (GOCI) is under development to provide a monitoring of ocean-color around the Korean Peninsula from geostationary platforms. It is planned to be loaded on Communication, Ocean, and Meteorological Satellite (COMS) of Korea. In this study, the radiometric model of GOCI, which is constructed based on the functional model of sub-system, is introduced. Non-linearity for each channel is analyzed in terms of linear gain and nonlinear gain by using the radiometric model. The non-linearity characteristic is validated by using test data which have been achieved during ground test at payload level. The non-linearity $G^3$/b shows identical characteristic for all channels.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.04a
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• pp.353-356
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• 2000

본 논문에서는 데이터 내의 비선형 속성을 보다 빠르고 정확하게 추출하기 위한 수정된 학습알고리즘의 비선형 주요 성분분석 신경망을 제안한다. 제안된 학습알고리즘은 신경망의 학습시에 과거의 속성을 반영하기 위한 모멘트 항이 추가된 학습기법이다. 이는 최적해로의 수렴에 따른 발전을 억제하여 그 수렴성능을 좀더 개선시키는 모멘텀의 장점을 그대로 살리기 위함이다. 제안된 학습알고리즘을 이용한 신경망을 128$\times$128 픽셀의 Lenna와 256$\times$128 픽셀의 차량 번호판 영상들을 대상으로 시뮬레이션 한 결과, 제안된 학습알고리즘이 기존의 비선형 주요성분 분석을 위한 신경망이나 선형속성을 가지는 역전파 알고리즘을 이용한 신경망보다 더욱 우수한 수렴 성능과 특징추출 성능이 있음을 확인하였다.

• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.361-368
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• 2004

The purpose of this study is to propose a new on-line nonlinear PCA(OL-NPCA) method for a nonlinear feature extraction from the incremental data. Kernel PCA(KPCA) is widely used for nonlinear feature extraction, however, it has been pointed out that KPCA has the following problems. First, applying KPCA to N patterns requires storing and finding the eigenvectors of a N${\times}$N kernel matrix, which is infeasible for a large number of data N. Second problem is that in order to update the eigenvectors with an another data, the whole eigenspace should be recomputed. OL-NPCA overcomes these problems by incremental eigenspace update method with a feature mapping function. According to the experimental results, which comes from applying OL-NPCA to a toy and a large data problem, OL-NPCA shows following advantages. First, OL-NPCA is more efficient in memory requirement than KPCA. Second advantage is that OL-NPCA is comparable in performance to KPCA. Furthermore, performance of OL-NPCA can be easily improved by re-learning the data.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.1
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• pp.53-59
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• 2016

Ultrasonic nonlinear evaluation is generally utilized for detection of not only defects but also microdamage such as corrosion and plastic deformation. Nonlinearity is determined by the amplitude ratio of primary wave second harmonic wave, and the results of its comparison are used for evaluation. Owing to the experimental features, the experimental nonlinearity result contains system nonlinearity and material nonlinearity. System nonlinearity is that which is unwanted by the user; hence, it acts as an error and interrupts analysis. In this study, a bulk wave mixing technique is implemented in order to minimize the system nonlinearity and obtain the reliable analysis results. The biggest advantage of this technique is that experimental nonlinearity contains less system nonlinearity than that for the conventional nonlinear ultrasonic technique. Theoretical and experimental verifications are performed in this study. By comparing the results of the bulk wave mixing technique with those of the conventional technique, the strengths, weaknesses, and application validity of the bulk wave mixing technique are determined.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.4
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• pp.531-538
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• 1998

In this paper the system performance degradation resulting from nonlinear transmitter power amplifier which is essential to increase the efficiency is analysed in a CDMA system. The power amplifier is modeled by its AM-AM, AM-PM characteristics. The effects of power amplifier's nonlinearity such as intersymbol interference, phase distonion on the RF system performance were visualized by examining the distorted time domain waveforms, signal vector constellation. And through the investigation of the power spectrum density of the transmitted signal, spectral regrowth or sideband regrowth which is result from amplitude distortion can be seen. All these characteristics result in BER performance degradation due to other user interferences and intersymbol interference. The analysis technique described here applies not only to power amplifier but also to any other nonlinear components such as mixers and switches. Also the effects of adjacent channel interference and supurious emission can be analysed between different systems.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05d
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• pp.333-338
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• 1996

강진에 의한 원전구조물의 동적해석시 지반의 비선형특성은 반드시 고려해야 할 사항이다. 지반의 비선형특성은 지반-구조계의 동적응답을 구하는 과정에서 가장 중요한 요소중의 하나며 이를 고려한 비선형 지진해석은 일반적으로 매우 복잡하고 정해를 구하기가 매우 어려운 문제다. 본 연구에서는 비선형 해법으로 널리 사용되고 있는 등가선형화방법을 사용하여 계측결과가 있는 TEPSCO 비선형 지진문제를 해석하였으며 이 방법의 정확도와 적용성을 분석하였다. 아울러 축대칭기법을 사용하여 비선형지진해석을 수행할때의 문제점에 관해서도 검토하였다.

• Korean Journal of Applied Biomechanics
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• v.18 no.1
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• pp.21-30
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• 2008

The purpose of this study was to investigate the variability to compare local dynamic stability via a linear and nonlinear analysis during walking. Twenty four elderly males, 12 healthy elderly and 12 patients with osteoarthritise walked on a treadmill for 100 consecutive strides. Lyapunov exponent and correlation dimension and coefficient variation were calculated for the kinematic parameters to determine the dynamic stability during walking. The linear measures indicated that the healthy elderly demonstrated significantly higher variability in the ankle joint displacement. The nonlinear analysis revealed that COD for the knee joint angle were higher in patient with osteoarthritise. There were no coincidence in results between linear and nonlinear techniques over two groups. In light of nonlinear analysis, it was concluded that patients with osteoathritise showed higher local instability during walking.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1B
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• pp.37-45
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• 2011

We studied noise influence on nonlinear chaotic system by using Logistic data series which is known as a typical nonlinear chaotic system. We regenerated Logistic data series by the method of adding noise according to noise level. And, we performed some analyses such as phase space reconstruction, correlation dimension, BDS statistics, and DVS Algorithms which are known as the methods of nonlinear deterministic or chaotic analysis. If we see the results of analysis, the characteristics of data series are gradually changed from nonlinear chaotic data series to random stochastic data series according to increasing noise level. We applied Low Pass Filter (LPF) and Kalman Filter techniques for the investigation of removing effect of the added noise to data series. Typical nonparametric method cannot distinguish nonlinear random series but the BDS statistic can distinguish the nonlinear randomness of the time series. Therefore this study used the BDS statistic which is well known as nonlinear statistical method for the investigation of randomness of time series for the effect of removing noise of data series. We found that Kalman filter is better method to remove the noise of chaotic data series even for high noise level.