• The Journal of the Korea Contents Association
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• v.3 no.3
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• pp.98-102
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• 2003

For elucidating the key role of hidden neurons in information processing of Multilayer perceptrons(MLPs), we prove that the correlation coefficient between weighted sums to hidden neurons decreases under element-wise nonlinear transformations. This is verified through training of MLPs for an isolated word recognition problem. From this result, we can say that the element-wise nonlinear functions reduces redundancy in the information contents of hidden neurons.

• ETRI Journal
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• v.20 no.2
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• pp.214-230
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• 1998

We investigate noise-induced transitions in active rotator model with a fluctuating threshold in the presence of an additive noise. The fluctuation of the threshold depends on the additive noise in a nonlinear fashion. In the white-noise limit of the fluctuation, the Fokker-Planck equation of the system reduces to that of the system with correlated linear fluctuation implying that the nonlinearity may be transformed into the correlation of linear noises. We also investigate the system with a nonlinear colored noise which depends on the additive noise as its square. The system shows a single peak, two peaks, and three peaks in its steady state probability distribution according to the noise intensities and the correlation time whose change leads to peak-creating, peak-splitting, and peak-merging transitions.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.8
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• pp.889-895
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• 2007

Quantifying dynamic stability is important to assessment of falling risk or functional recovery for leg injured people. Human locomotion is complex and known to exhibit nonlinear dynamical behaviors. The purpose of this study is to quantify major joints of the body using chaos analysis during walking. Time series of the chaotic signals show how gait patterns change over time. The gait experiments were carried out for ten young males walking on a motorized treadmill. Joint motions were captured using eight video cameras, and then three dimensional kinematics of the neck and the upper and lower extremities were computed by KWON 3D motion analysis software. The correlation dimension and the largest Lyapunov exponent were calculated from the time series to quantify stabilities of the joints. This study presents a data set of nonlinear dynamic characteristics for eleven joints engaged in normal level walking.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.258-262
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• 1996

The physiological systems have nonlinear complex phenomena. Expecially, the flow of capillary blood vessel has a nonlinear dynamic system. Thus, this study analyzes nonlinear characteristics of the flow of capillary blood vessel in physiological systems using chaotic tools(phase space reconstruction, correlation dimension, largest lyapunov exponent). Experimental data have been acquired from examining 10 rabbits. The results of chaotic analysis showed a decreasing largest lyapunov exponent and correlation dimension according to increasement glocose index. And we also know the chaotic behavior.

• Bulletin of the Korean Chemical Society
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• v.9 no.1
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• pp.36-40
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• 1988

The time correlation functions of concentration fluctuations due to the random forces near the steady state are evaluated for a general two-component nonlinear chemical system by solving the corresponding two dimensional Fokker-Planck equation. The approximate method of solving the Fokker-Planck equation is based on the eigenfunction expansion and the corresponding eigenvalues for both the linear and nonlinear Fokker-Planck operators are obtained near the steady state. The general results are applied to the Lotka model near the oscillatory marginal steady state and the comparison is made between linear and nonlinear cases.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.149-152
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• 1996

In this paper, the authors propose a new method for linearizing a nonlinear dynamical system by use of Volterra kernel of the nonlinear system. The authors have recently obtained a new method for measuring Volterra kernels of nonlinear control systems by use of a pseudo-random M-sequence and correlation technique. In this method, an M-sequence is applied to the nonlinear system and the crosscorrelation function between the input and the output gives us every crosssection of Volterra kernels up to 3rd order. Once we can get Volterra kernels of nonlinear system, we can construct a linearization method of the nonlinear system. Simulation results show good agreement between the observed results and the theoretical considerations.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.104-112
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• 2001

Simply, Nonlinear dynamics theory means the complicated and noise-like phenomena originated form nonlinearity involved in deterministic dynamical system. An almost all the natural signals have nonlinear property. However, there exist few analysis software tool or package for a research and development of applications. We develop nonlinear time series analysis simulator is to provide a common and useful tool for this purpose and to promote research and development of nonlinear dynamics theory. This simulator is consists of the following four modules such as generation module, preprocessing module, analysis module and ICA module. In this paper, we applied to Electroencephalograph (EEG), as it turned out, our simulator is able to analyze nonlinear time series. Besides, we could get the useful results using the various parameters. These results are used to diagnostic the brain diseases.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.5
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• pp.713-718
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• 2016

Predicting precise specifications of differential mixed-signal circuits is a difficult problem, because analytically derived correlation between process variations and conventional specifications exhibits the limited prediction accuracy due to the phase unbalance, for most self-tests. This paper proposes an efficient prediction technique to provide accurate specifications of differential mixed-signal circuits in a system-on-chip (SoC) based on a nonlinear statistical nonlinear regression technique. A spectrally pure sinusoidal signal is applied to a differential DUT, and its output is fed into another differential DUT through a weighting circuitry in the loopback configuration. The weighting circuitry, which is employed from the previous work [3], efficiently produces different weights on the harmonics of the loopback responses, i.e., the signatures. The correlation models, which map the signatures to the conventional specifications, are built based on the statistical nonlinear regression technique, in order to predict accurate nonlinearities of individual DUTs. In production testing, once the efficient signatures are measured, and plugged into the obtained correlation models, the harmonic coefficients of DUTs are readily identified. This work provides a practical test solution to overcome the serious test issue of differential mixed-signal circuits; the low accuracy of analytically derived model is much lower by the errors from the unbalance. Hardware measurement results showed less than 1.0 dB of the prediction error, validating that this approach can be used as production test.

• Journal of the Optical Society of Korea
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• v.19 no.3
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• pp.241-247
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• 2015

The double-random phase encryption (DRPE) algorithm is a robust technique for image encryption, due to its high speed and encoding a primary image to stationary white noise. Recently it was reported that DRPE in the Fresnel domain can achieve a better avalanche effect than that in Fourier domain, which means DRPE in the Fresnel domain is much safer, to some extent. Consequently, a method based on DRPE in the Fresnel domain would be a good choice. In this paper we present an image-authentication method which uses only partial phase information from a double-random-phase-encrypted image in the Fresnel domain. In this method, only part of the phase information of an image encrypted with DRPE in the Fresnel domain needs to be kept, while other information like amplitude values can be eliminated. Then, with the correct phase keys (we do not consider wavelength and distance as keys here) and a nonlinear correlation algorithm, the encrypted image can be authenticated. Experimental results demonstrate that the encrypted images can be successfully authenticated with this partial phase plus nonlinear correlation technique.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.5
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• pp.424-430
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• 2000

In order to develop an ultrasonic evaluation method for properties degradation of high temperature materials, a number of Cr-Mo-V steel samples were heat-treated and their damage mechanism was examined. Ultrasonic parameters such as velocity, attenuation, and more recently developed nonlinear acoustic parameter were measured. The nonlinear acoustic parameter was found to be most sensitive to material degradation mainly attributed to the precipitation of impurities in grain boundaries. When compared to the electrical resistivity results, the nonlinear parameters showed similar behavior. There existed a relatively good correlation between the nonlinear parameter and the fracture appearance transition temperature (FATT) obtained by Charpy V-notch impact test. Based on the relationship between the FATT and the fracture toughness ($K_{IC}$), correlation between the nonlinear parameter and $K_{IC}$ was established.