• Journal of Sensor Science and Technology
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• v.25 no.1
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• pp.71-78
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• 2016

PPG signal measured by pulse oximeter can measure pulse and the oxygen saturation of arterial blood. But the PPG signal is distorted by finger movement or other movement in the body. To detect pulse from the PPG signal with motion artifact, we use band pass filter(BPF), Independent component analysis(ICA) and nonlinear autocorrelation(NAC). BPF is used to remove DC component and high frequency noise in the PPG signal with motion artifacts. ICA is used to separate pulse signal and motion artifact. However, pulse signal separated by ICA have no choice but to accompany signal distortion because pulse signal and motion artifact are not completely independent. So, we use nonlinear autocorrelation to emphasize the pure pulse signal from the distorted signal.

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.731-740
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• 1999

Autocorrelation function is widely used as a tool measuring linear dependence of hydrologic time series. However, it may not be appropriate for choosing decorrelation time or delay time ${\tau}_d$ which is essential in nonlinear dynamics domain and the mutual information have recommended for measuring nonlinear dependence of time series. Furthermore, some researchers have suggested that one should not choose a fixed delay time ${\tau}_d$ but, rather, one should choose an appropriate value for the delay time window ${\tau}_d={\tau}(m-1)$, which is the total time spanned by the components of each embedded point for the analysis of chaotic dynamics. Unfortunately, the delay time window cannot be estimated using the autocorrelation function or the mutual information. Basically, the delay time window is the optimal time for independence of time series and the delay time is the first locally optimal time. In this study, we estimate general dependence of hydrologic time series using the C-C method which can estimate both the delay time and the delay time window and the results may give us whether hydrologic time series depends on its linear or nonlinear characteristics which are very important for modeling and forecasting of underlying system.

• Journal of the Optical Society of Korea
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• v.3 no.1
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• pp.27-31
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• 1999

The two-photon absorption of a SiC photodiode was utilized to obtain autocorrelation signals of the pulses from a mode-locked Rh6G dye laser. The autocorrelation signals were in good agreement with those obtained by a conventional autocorrelator using a second harmonic crystal and photomultiplier tube. The sensitivity of the autocorrelator with the SiC photodiode was about $4{\times}10^3 {(mW)}^2$ . From these results it was demonstrated that the SiC photodiode is suitable as a nonlinear device for an autocorrelation measurement in the visible range.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1539-1547
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• 2014

In this paper we apply the autoregressive process to the nonlinear quantile regression in order to infer nonlinear quantile regression models for the autocorrelated data. We propose a kernel method for the autoregressive data which estimates the nonlinear quantile regression function by kernel machines. Artificial and real examples are provided to indicate the usefulness of the proposed method for the estimation of quantile regression function in the presence of autocorrelation between data.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.35 no.3
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• pp.216-222
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• 2002

Autocorrelation in time series data can affect statistical inference in correlation or regression analyses. To improve a regression model from which the residuals are autocorrelated, Yule-Walker method, nonlinear least squares estimation, maximum likelihood method and 'prewhitening' method have been used to estimate the parameters in a regression equation. This study reviewed on the estimation methods of preventing spurious correlation in the presence of autocorrelation and applied the former three methods, Yule-Walker, nonlinear least squares and maximum likelihood method, to a 20-year real data set. Monte carlo simulation was used to compare the three parameter estimation methods. However, the simulation results showed that the mean squared error distributions from the three methods simulated do not differ significantly.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.949-954
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• 2009

The autoregressive process is applied in this paper to kernel regression in order to infer nonlinear models for predicting responses. We propose a kernel method for the autoregressive data which estimates the mean function by kernel machines. We also present the model selection method which employs the cross validation techniques for choosing the hyper-parameters which affect the performance of kernel regression. Artificial and real examples are provided to indicate the usefulness of the proposed method for the estimation of mean function in the presence of autocorrelation between data.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.47-52
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• 2010

For cryptographic systems, nonlinearity is crucial since most linear systems are easily decipherable. C.Bracken, Z.Zhaetc., propose the APN(Almost Perfect Nonlinear) functions with the properties similar to those of the bent functions with perfect nonlinearity. We design two kinds of new code sequence generating algorithms using the above APN functions. And we find that the out of phase ${\tau}\;{\neq}\;0$, autocorrelation functions, $R_{ii}(\tau)$ and the crosscorrelation functions, $R_{ik}(\tau)$ of the binary code sequences generated by two new algorithms over GF(2), have three values of {-1, $-1-2^{n/2}$, $-1+2^{n/2}$}. We also find that the out of phase ${\tau}\;{\neq}\;0$, autocorrelation functions, $R_{p,ii}(\tau)$ and the crosscorrelation functions, $R_{p,ik}(\tau)$ of the nonbinary code sequences generated by the modified algorithms over GF(p), $p\;{\geq}\;3$, have also three values of {$-1+p^{n-1}$, $-1-p^{(n-1)/2}+p^{n-1}$, $-1+p^{(n-1)/2}p^{n-1}$}. We show that these code sequences have the characteristics of the correlation functions similar to those of Gold code sequences.

• Journal of Korean Society for Quality Management
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• v.50 no.3
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• pp.349-371
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• 2022

Purpose: Compared to the rapid growth rate of the domestic automotive LED industry so far, the predictive analysis method for demand forecasting or market outlook was insufficient. Accordingly, product characteristics are analyzed through the life trend of LEDs for automotive exterior lamps and the relative strengths of p and q using the Bass model. Also, future demands are predicted. Methods: We used sales data of a leading company in domestic market of automotive LEDs. Considering the autocorrelation error term of this data, parameters m, p, and q were estimated through the modified estimation method of OLS and the NLS(Nonlinear Least Squares) method, and the optimal method was selected by comparing prediction error performance such as RMSE. Future annual demands and cumulative demands were predicted through the growth curve obtained from Bass-NLS model. In addition, various nonlinear growth curve models were applied to the data to compare the Bass-NLS model with potential market demand, and an optimal model was derived. Results: From the analysis, the parameter estimation results by Bass-NLS obtained m=1338.13, p=0.0026, q=0.3003. If the current trend continues, domestic automotive LED market is predicted to reach its maximum peak in 2021 and the maximum demand is $102.23M. Potential market demand was $1338.13M. In the nonlinear growth curve model analysis, the Gompertz model was selected as the optimal model, and the potential market size was $2864.018M. Conclusion: It is expected that the Bass-NLS method will be applied to LED sales data for automotive to find out the characteristics of the relative strength of q/p of products and to be used to predict current demand and future cumulative demand.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.1
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• pp.53-59
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• 2000

We propose a modified nonlinear fiber optic interferometer which can serve to generate binary optical pulse sequences for CDMA networks, and to decode them. In one arm cross-phase modulation between a CW signal and a counter- or copropagating high-power pulse takes place in sequences of segment connected via VDM couplers. Preliminary experimental results on code generation as well as autocorrelation and crosscorrelation are presented, using Sagnac interferometer. As we expected, the experimental results show that the outputs of the interferometer device are not summed simply on the basis of power, but the sin-squared version of it. Arbitrary codes can in principle be implemented.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1797-1798
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• 2007

In field of voice pathology, diverse statistics extracted form pitch estimation were commonly used to assess voice quality. In this study, we proposed robust pitch detection algorithm which can estimate pitch of pathological voices in benign vocal fold lesions. we also compared our proposed algorithm with three established pitch detection algorithms; autocorrelation, simplified inverse filtering technique, and nonlinear state-space embedding methods. In the database of total pathological voices of 99 and normal voices of 30, an analysis of errors related with pitch detection was evaluated between pathological and normal voices, or among the types of pathological voices. According to the results of pitch errors, gross pitch error showed some increases in cases of pathological voices; especially excessive increase in PDA based on nonlinear time-series. In an analysis of types of pathological voices classified by aperiodicity and the degree of chaos, the more voice has aperiodic and chaotic, the more growth of pitch errors increased. Consequently, it is required to survey the severity of tested voice in order to obtain accurate pitch estimates.