• The Journal of the Acoustical Society of Korea
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• v.19 no.1E
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• pp.22-26
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• 2000

In this paper, the DS/CDMA PN code acquisition system with nonlinear transmitter power amplifier based on digital matched filter (DMF) which has the rapid acquisition time is presented and the performance is evaluated in terms of mean acquisition time, detection probability, and signal to interference under multiuser environment. The performance is presented with respect to the output backoff of the nonlinear amplifier and the correlation window.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.61-69
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• 1995

The diagnosis has an very important role in curing dementia. But there was not the effective method to diagnose it until now. In this paper we analyzed the EEG in Alzheimer's disease and normal control groups to differentiated them by nonlinear parameter such as the correlation dimension. And we propose the nonlinear analysis of EEG in Alzheimer's disease as a useful tool of early diagnosis of it.

• Journal of applied mathematics & informatics
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• v.7 no.1
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• pp.269-278
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• 2000

A Boolean function generates a binary sequence which is frequently used in a stream cipher. There are number of critical concepts which a Boolean function, as a key stream generator in a stream cipher, satisfies. These are nonlinearity, correlation immunity, balancedness, SAC(strictly avalanche criterion), PC(propagation criterion) and so on. In this paper, we present the algorithms for generating random nonlinear combining functions satisfying given correlation immune order and nonlinearity. These constructions can be applied for designing the key stream generators. We use Microsoft Visual C++6.0 for our program.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1997.04a
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• pp.265-272
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• 1997

This paper presents the result of an international cooperative research on the post-correlation analysis of forced vibration tests and the prediction of earthquake responses of a large-scale seismic test structure. Through the post-correlation analysis, the properties of the soil layers are revised so that the best correlation in the responses may be obtained compared with the measured force vibration test data. Utilizing the revised soil properties as the initial linear values, the seismic responses are predicted for an earthquake using the equivalent linearlization technique based on the specified strain dependent characteristics of the shear moduli and damping ratios. It has been found that the predicted responses by the equivalent nonlinear procedure are in excellent agreement with the observed responses, which those using the initial properties are fairly off from the measured results.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.2
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• pp.109-113
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• 2002

Van de Vusse reactor is known as a highly nonlinear chemical process and has been considered by a number of researchers as a benchmark problem for nonlinear chemical process. Various identification methods for nonlinear system are also verified by applying these methods to Van de Vusse reactor. From the point of view of identification, only the Volterra kernel of second order has been obtained until now. In this paper, the authors show that Volterra kernels of nonlinear Van de Vusse reactor of up to 3rd order are obtained by use of M-sequence correlation method. A pseudo-random M-sequence is applied to Van de Vusse reactor as an input and its output is measured. Taking the crosscorrelation function between the input and the output, we obtain up to 3rd order Volterra kernels, which is the highest order Volterra kernel obtained until now for Van de Vusse reactor. Computer simulations show that when Van de Vusse chemical process is identified by use of up to 3rd order Volterra kernels, a good agreement is observed between the calculated output and the actual output.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.161-164
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• 1996

The authors have recently proposed a new method for identifying Volterra kernels of nonlinear control systems by use of M-sequence and correlation technique. A specially chosen M-sequence is added to the nonlinear system to be identified, and the crosscorrelation function between the input and output is calculated. Then every crosssection of Volterra kernels up to 3rd order appears at a specified delay time point in the crosscorrelation. This method is applied to a saturation-type nonlinear feedback control system of mechanical-electrical servo system having torque saturation nonlinearity. Simulation experiments show that we can obtain Volterra kernels of saturation-type nonlinear system, and a good agreement is observed between the observed output and the calculated one from the measured Volterra kernels.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.150-154
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• 1993

A new method is proposed for obtaining Volterra kernals of a nonlinear system by use of a nonlinear systems by use of pseudorandom M-sequences and correlation technique. M-sequence is applied to a nonlinear technique. M-sequence is applied to a nonlinear system and the crosscorrelation function between the input and the output displays not only the linear impulse response of the linear part of the system, but also crosssections of the Volterra kernals of nonlinear system. Simulations are carried out for up to 3rd order Volterra kernal, and the results show a good agreement with the theoretical considerations.

• Communications for Statistical Applications and Methods
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• v.31 no.2
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• pp.247-262
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• 2024

In this paper, we explore nonlinear sufficient dimension reduction (SDR) methods, with a primary focus on establishing a foundational framework that integrates various nonlinear SDR methods. We illustrate the generalized sliced inverse regression (GSIR) and the generalized sliced average variance estimation (GSAVE) which are fitted by the framework. Further, we delve into nonlinear extensions of inverse moments through the kernel trick, specifically examining the kernel sliced inverse regression (KSIR) and kernel canonical correlation analysis (KCCA), and explore their relationships within the established framework. We also briefly explain the nonlinear SDR for functional data. In addition, we present practical aspects such as algorithmic implementations. This paper concludes with remarks on the dimensionality problem of the target function class.

• Korean Journal of Biological Psychiatry
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• v.4 no.1
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• pp.67-73
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• 1997

The changes of electroencephalogram(EEG) in patients with dementia are most commonly studied by analyzing power or magnitude in certain traditionally defined frequency bands. However because of the absence of an identified metric which quantifies the complex amount of information, there are many limitations in using such a linear method. According to chaos theory, irregular signals of EEG can also result from low dimensional deterministic chaos. Chaotic nonlinear dynamics in the EEG can be studied by calculating the correlation dimension. The authors have analyzed EEG epochs from three patients with dementia of Alzheimer type and three matched control subjects. The multichannel correlation dimension is calculated from EEG epochs consisting of 15 channels with 16,384 data points per channel. The results showed that patients with dementia of Alzheimer type had significantly lower correlation dimension than non-demented controls on 12 channels. Topographic analysis showed that the correlation dimensions were significantly lower in patients with Alzheimer's disease on frontal, temporal, central, and occipital head regions. These results show that brains of patients with dementia of Alzheimer type have a decreased complexity of electrophysiological behavior. We conclude that the nonlinear analysis such as calculating correlation dimension can be a promising tool for detecting relative changes in the complexity of brain dynamics.

• Phonetics and Speech Sciences
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• v.2 no.1
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• pp.113-120
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• 2010

In this paper, we investigate the acoustic characteristics of sustained voices from normal subjects and patients with laryngeal pathologies. Perturbation methods (including jitter and shimmer), signal-to-noise ratio (SNR), and nonlinear dynamic methods (such as correlation dimension) are used to analyze normal and pathological voices. We find that jitter does not statistically discriminate between normal and pathological voices, but a significant difference is found for shimmer, SNR, and correlation dimension. The results suggest that nonlinear dynamic analysis may be valuable for the analysis of normal and pathological voices but perturbation analysis should be applied with caution for pathological voice analysis.