• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.6
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• pp.71-78
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• 1989

The imput-output relations for nonlinear systems can be explicitly represented by the Volterra series and they can be characterized by the Volterra kernels. This study is concerned with modeling an elastomer force-displacement relation due to step inputs by utilizing the truncated Volterra series. Since it is practically impossible to apply step inputs that have infinite slope at zero time, the loads due to constant penetration(displacement) rate followed by constant penetration inputs are measured as an alternative approach and estimated for step inputs and then utilized for the truncated Volterra series models. One second order and one third order truncated Volterra series models have been employed to model the force-displacement relation which is one of the prominent properties to characterize the viscoelastic material. The third order truncated Volterra series model has better results, compared with those of the second order truncated Volterra series model.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.8
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• pp.1901-1906
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• 1995

The frequency response functions of systems incorporating a non-linear cubic stiffness subject to sinusoidal excitation are derived using the Volterra series and the convergence characteristics investigated. It is shown that the series representation of the frequency response functions converges only when the sinewave input amplitude is within a certain range. Within the range of convergence the frequency response function based on the Volterra series approaches the analytical one as more higher order frequency response function terms are included. Proposed is a criterion for the studies systems to predict approximately the range of sinewave input amplitude for which the series representation of the frequency response functions converges.

• The Journal of the Acoustical Society of Korea
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• v.11 no.6
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• pp.15-22
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• 1992

i.i.d 신호의고차 모멘트와 스펙트럼의 성질에 대하여 4차까지 고찰하였으며 이의 결과를 이용하 여 2차 Volterra 급수로 표시되고, i.i.d. 입력 신호를 갖는 시불변 비선형 시스테므이 파라메타들을 추정 하는 알고리즘을 시간 영역과 주파수 영역에서 각각 제안하였다. 비록 2차 Volterra 급수가 i.i.d. 입력 신호에 대하여 orthogonal 모델이 아닐지라도 입력 신호의 각종 시간지연에 대한 모멘트나 역행렬의 계 산등이 요구되지 않으며 선형 전달함수와 2차 전달함수를 추정할 수 있는 알고리즘이 존재하는 것을 보 았다.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.5
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• pp.59-65
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• 2012

In this paper, we investigate the compressed sensing (CS) algorithms for modeling a super-resolution near-field structure (super-RENS) disc system with a sparse Volterra filter. It is well known that the super-RENS disc system has severe nonlinear inter-symbol interference (ISI). A nonlinear system with memory can be well described with the Volterra series. Furthermore, CS can restore sparse or compressed signals from measurements. For these reasons, we employ the CS algorithms to estimate a sparse super-RENS read-out channel. The evaluation results show that the CS algorithms can efficiently construct a sparse Volterra model for the super-RENS read-out channel.

• Journal of the Society of Naval Architects of Korea
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• v.57 no.5
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• pp.305-311
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• 2020

This study presents a probabilistic time series forecast of ship structural response using Bayesian inference combined with Volterra linear model. The structural response of a ship exposed to irregular wave excitation was represented by a linear Volterra model and unknown uncertainties were taken care by probability distribution of time series. To achieve the goal, Volterra series of first order was expanded to a linear combination of Laguerre functions and the probability distribution of Laguerre coefficients is estimated using the prepared data by treating Laguerre coefficients as random variables. In order to check the validity of the proposed methodology, it was applied to a linear oscillator model containing damping uncertainties, and also applied to model test data obtained by segmented hull model of 400,000 DWT VLOC as a practical problem.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.4
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• pp.274-282
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• 2014

Time series of the dynamic response of a slender marine structure was predicted using quadratic Volterra series. The wave-structure interaction system was identified using the NARX(Nonlinear Autoregressive with Exogenous Input) technique, and the network parameters were determined through the supervised training with the prepared datasets. The dataset used for the network training was obtained by carrying out the nonlinear finite element analysis on the freely standing riser under random ocean waves of white noise. The nonlinearities involved in the analysis were both large deformation of the structure under consideration and the quadratic term of relative velocity between the water particle and structure in Morison formula. The linear and quadratic frequency response functions of the given system were extracted using the multi-tone harmonic probing method and the time series of response of the structure was predicted using the quadratic Volterra series. In order to check the applicability of the method, the response of structure under the realistic ocean wave environment with given significant wave height and modal period was predicted and compared with the nonlinear time domain simulation results. It turned out that the predicted time series of the response of structure with quadratic Volterra series successfully captures the slowly varying response with reasonably good accuracy. It is expected that the method can be used in predicting the response of the slender offshore structure exposed to the Morison type load without relying on the computationally expensive time domain analysis, especially for the screening purpose.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.3 s.43
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• pp.33-42
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• 2005

Frequency domain Volterra model is applied to nonlinear parameter identification procedure for dynamic systems modeled by nonlinear function. The frequency domain Volterra kernels, which correspond io linear, quadratic, and cubic transfer functions in lime domain, are incorporated in nonlinear parametric identification procedure. The nonlinear transfer functions, which can be derived from the Volterra series representation of the nonlinear differential equation of the system by Schetzen's method(1980), are directly used for modeling input output relation. The error is defined by the difference between the observed output and the estimated output which is calculated by substituting the observed input to nonlinear frequency domain model. The system parameters are searched by minimizing the error. Volterra model guarantees enough accuracy and convergence and the estimated coefficients have a good agreement with their actual values not only in the linear frequency region but also in the legion where the $2^{nd}\;or\;3^{rd}$ order nonlinearity is dominant.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.6
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• pp.23-28
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• 2020

A non-linear vibration isolation system composed of a non-linear spring and a linear damper was presented in a previous study. The advantage of the proposed isolator is the simple structure of the system. When the base of the isolator is harmonically excited, the response component of the mass at the excitation frequency was approximated using three different methods: linear approximation, harmonic balance, and higher-order frequency response functions (FRFs). The method using higher-order FRFs produces significantly more accurate results compared with the other methods. The error between the exact and approximate responses does not increase monotonously with the excitation amplitude and is less than 2%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.6
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• pp.1231-1243
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• 1997

Digital satellite communication channels have nonlinearities with memory due to saturation characteristics of traveling wave tube amplifier in the satellite and transmitter/receiver linear filters. In this paper, we propose a network structure and a learning algorithm for complex pi-sigma network (CPSK) and exploit CPSN in the problem of equalization of nonlinear satellite channels. The proposed CPSN is a complex-valued extension of real-valued pi-sigma network that is a higher-order feedforward network with fast learning while greatly reducing network complexity by utilizing efficient form of polynomials for many input variables. The performance of the proposed CPSN is demonstrated by computer simulations on the equalization of complex-valued QPSK input symbols distorted by a nonlinear channel modeled as a Volterra series and additive noise. The results indicate that the CPSN shows good equalization performance, fast convergence, and less computations as compared to conventional higher-order models such as Volterra filters.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.7 no.1
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• pp.116-125
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• 1995

Higher order nonlinear transfer functions are applied to model the nonlinear responses obtained Inn dynamic analysis of single degree of freedom systems (SDOF) subjected to wave and current loadings. The structural systems are subjected to single harmonic, two wave combination and irregular wave loading. Three different sources of nonlinearities are examined for each of the wave loading condition and it is shown that the nonlinear response appear at the resonance frequencies of the SDOF even when virtually no wave energy exists at those resonance frequencies. Higher order nonlinear transfer functions based on Volterra series representation are used to model the nonlinear responses mainly f3r the flexible systems and clearly shows the degrees of nonlinearity either as quadratic or cubic.