• Journal of Korean Society of Forest Science
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• v.88 no.1
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• pp.47-54
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• 1999

To estimate optimal tree diameter and height growth function in Pinus thunbergii stands with site index of 12 class, quoted from two linear models of linear transformation(1) and linear transformation (2) and four non-linear models of exponential, Gompertz, Chapman-Richards, and Weibull etc.. Analyzed correlation among the estimated tree diameter and height by these function models, and observed diameter and height growth were compared. In the results of tree diameter and height growth estimation by stand age, non-linear models showed better appropriation than linear model and Chapman-Richards model was most fitted for tree height growth but few, if any, differences among their nonlinear models. Therefore, it is consider to be much more study about non-linear model to estimate tree diameter and height growth in the actual stands hereafter.

• Genomics & Informatics
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• v.17 no.4
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• pp.39.1-39.20
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• 2019

Analyzing patterns in data points embedded in linear and non-linear feature spaces is considered as one of the common research problems among different research areas, for example: data mining, machine learning, pattern recognition, and multivariate analysis. In this paper, data points are heterogeneous sets of biosequences (composite data points). A composite data point is a set of ordinary data points (e.g., set of feature vectors). We theoretically extend the derivation of the largest generalized eigenvalue-based distance metric D_ij(γ₁) in any linear and non-linear feature spaces. We prove that D_ij(γ₁) is a metric under any linear and non-linear feature transformation function. We show the sufficiency and efficiency of using the decision rule $\bar{{\delta}}_{{\Xi}i}$(i.e., mean of D_ij(γ₁)) in classification of heterogeneous sets of biosequences compared with the decision rules min_𝚵iand median_𝚵i. We analyze the impact of linear and non-linear transformation functions on classifying/clustering collections of heterogeneous sets of biosequences. The impact of the length of a sequence in a heterogeneous sequence-set generated by simulation on the classification and clustering results in linear and non-linear feature spaces is empirically shown in this paper. We propose a new concept: the limiting dispersion map of the existing clusters in heterogeneous sets of biosequences embedded in linear and nonlinear feature spaces, which is based on the limiting distribution of nucleotide compositions estimated from real data sets. Finally, the empirical conclusions and the scientific evidences are deduced from the experiments to support the theoretical side stated in this paper.

• Journal of the Korean Mathematical Society
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• v.48 no.1
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• pp.133-146
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• 2011

We employ a hyperbolic tangent function to construct nonlinear transformations which are useful in numerical evaluation of weakly singular integrals and Cauchy principal value integrals. Results of numerical implementation based on the standard Gauss quadrature rule show that the present transformations are available for the singular integrals and, in some cases, give much better approximations compared with those of existing non-linear transformation methods.

• Communications for Statistical Applications and Methods
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• v.30 no.2
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• pp.163-178
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• 2023

GARCH-X(1, 1) model specifies that conditional variance follows an AR(1) process and includes a past exogenous variable. This study proposes a new class from that model by allowing a more general (non-linear) variance function to follow an AR(1) process. The functions applied to the variance equation include exponential, Tukey's ladder, and Yeo-Johnson transformations. In the framework of normal and student-t distributions for return errors, the empirical analysis focuses on two stock indices data in developed countries (FTSE100 and SP500) over the daily period from January 2000 to December 2020. This study uses 10-minute realized volatility as the exogenous component. The parameters of considered models are estimated using the adaptive random walk metropolis method in the Monte Carlo Markov chain algorithm and implemented in the Matlab program. The 95% highest posterior density intervals show that the three transformations are significant for the GARCHX(1, 1) model. In general, based on the Akaike information criterion, the GARCH-X(1, 1) model that has return errors with student-t distribution and variance transformed by Tukey's ladder function provides the best data fit. In forecasting value-at-risk with the 95% confidence level, the Christoffersen's independence test suggest that non-linear models is the most suitable for modeling return data, especially model with the Tukey's ladder transformation.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.628-632
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• 2001

We propose time-frequency (TF) tools for analyzing linear time-varying (LTV) systems and nonstationary random processes. Obtained warping the narrowband Weyl symbol (WS) and spreading function (SF), the new TF tools are useful for analyzing LTV systems and random processes characterized by generalized frequency shifts, This new Weyl symbol (WS) is useful in wideband signal analysis. We also propose WS an tools for analyzing systems which produce dispersive frequency shifts on the signal. We obtain these generalized, frequency-shift covariant WS by warping conventional, narrowband WS. Using the new, generalized WS, we provide a formulation for the Weyl correspondence for linear systems with instantaneous of linear signal transformation as weighted superpositions of non-linear frequency shifts on the signal. Application examples in signal and detection demonstrate the advantages of our new results.

• Journal of Biomedical Engineering Research
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• v.28 no.2
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• pp.199-204
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• 2007

In digital radiography, to improve the contrast of digital radiography image, the multi-scale nonlinear amplification algorithm based on unsharp masking is one of the major image enhancement algorithms. In this paper, we used the Laplacian pyramid to decompose a digital radiography(DR) image. In our simulation, the DR image was decomposed into seven layers and the coefficients of the each layer was amplified with nonlinear function. We also imported a noise containment algorithm to limit noise amplification. To enhance the contrast of image, we proposed a new adaptive non-linear gain amplification coefficients. As a result of having applied to some clinical data, a detail visibility was improved significantly without unacceptable noise boosting. Images that acquired with the proposed adaptive non-linear gain coefficients have shown superior quality to those that applied similar gain control method and expected to be accepted in the clinical applications.

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2524-2529
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• 2008

The thermal system like a combustion chamber is believed to experience a significant instability problem with vibration in case that the thermal energy or the acoustic energy are transformed into a different form through a relevant path. This study deals with a numerically- predicted, Thermoacoustic instability in a Rijke tube by using a non-linear model for a heat source. The heating part where the energy transformation occurs actively is modeled after simulating two-dimensional cylinder case with constant surface temperature, and a nonlinear model that accounts for the transfer function of magnitude- and phase-characteristics is properly implemented so as to be dependent on the pulsation strength in the tube. The heat source model is observed to result in equivalent Thermoacoustic instabilities in the Rijke tube except low flow-rate cases in which the natural convection is dominant.

• Proceedings of the KIEE Conference
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• 2002.06a
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• pp.161-165
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• 2002

The paper presents a diagnostic tool for analyzing the bit intermodulation in D/A converter. Bit intermodulation cause linearity errors which degrade the performance of the converter. A linear transformation of the Walsh transform of the integrated non-linearity diagram is shown to be sufficient to extract the bit intermodulation terms and their noise sensitivity. Practical applicability of the proposed method is shown by measurement.

• 전기의세계
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• v.31 no.1
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• pp.59-67
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• 1982

This paper suggests easy stabilization methods for linear time-varying systems with delay in the state. While existing methods employ the function space concept, the methods introduced in this paper transform the delay systems into the non-delay systems so that the well known methods for finite dimensional systems can be utilized. Particularly the intervalwise predictor is introduced and shown to satisfy an ordinary system. Control laws stabilizing the non-delay systems satisfied by this predictor will be shown to at least pointwise stabilize the delay systems with the additional strong possibility of true stabilization. In order to combine two steps of the predictor method, first transformation and then stabilization, an intervalwise regulator problem is suggested whose optimal control laws incorporate the intervalwise predictor as an integral part and also at least pointwise stabilize the delay systems. Since the above mentioned methods render the periodic feedback gains for time invariant systems the pointwise predictor and regulator are introduced in order to obtain the constant feedback gains, with additional stability properties. The control laws given in this paper are perhaps simplest and easiest to implement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2207-2216
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• 2012

Recently, wireless Internet environment with mobile phones and wireless sensor networks with severe resource restrictions have been actively studied. Moreover, an overall security issues are essential to build a reliable and secure sensor network. One of secure solution is to develop a fast cryptographic algorithm for data encryption. Therefore, we propose a 128-bit stream cipher, AA128 which has efficient implementation of software and hardware and is suitable for real-time applications such as wireless Internet environment with mobile phones, wireless sensor networks and Digital Right Management (DRM). AA128 is stream cipher which consists of 278-bit ASR and non-linear transformation. Non-linear transformation consists of Confusion Function, Nonlinear transformation(SF0 ~ SF3) and Whitening. We show that the proposed stream cipher AA128 is faster than AES and Salsa20, and it satisfies the appropriate security requirements. Our hardware simulation result indicates that the proposed cipher algorithm can satisfy the speed requirements of real-time processing applications.