• Journal of the Korean GEO-environmental Society
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• v.12 no.4
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• pp.53-63
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• 2011

Selection or generation of appropriate input ground motion is very important in performing a dynamic analysis. In Korea, it is a common practice to use recorded strong ground motions or artificial motions. The recorded motions show non-stationary characteristics, which is a distinct property of all earthquake motions, but have the problem of not matching the design response spectrum. The artificial motions match the design spectrum, but show stationary characteristics. This study generated ground motions that preserve the non-stationary characteristics of a real earthquake motion, but also matches the design spectrum. In the process, an impulse function-based algorithm that adjusts a given time series in time domain such that it matches the target response spectrum is used. Application of the algorithm showed that it can successfully adjust any recorded motions to match the target spectrum and also preserve the non-stationary characteristics. The modified motions are used to perform a series of nonlinear site response analyses. It is shown that the results using the adjusted motions result in more reliable estimates of ground vibration. It is thus recommended that the newly adjusted motions be used in practice instead of original recorded motions.

• Smart Structures and Systems
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• v.20 no.3
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• pp.263-272
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• 2017

This paper presents the time response of a mixed vibration system with the viscous damping and the hysteretic damping. There are two ways to derive the time response of such a vibration system. One is an analytical method, using the contour integral of complex functions to compute the inverse Fourier transforms. The other is an approximate method in which the analytic functions derived by Hilbert transform are expressed in the state space representation, and only the effective eigenvalues are used to efficiently compute the transient response. The unit impulse responses of the two methods are compared and the change in the damping properties which depend on the viscous and hysteretic damping values is investigated. The results showed that the damping properties of a mixed damping vibration system do not present themselves as a linear combination of damping properties.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.4
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• pp.122-128
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• 2002

In this paper dynamic responses of an engine, which is supported by hydraulic mount, to throttle tip-in/Tip out are analyzed. Because the hydraulic mounts have non-linearity that the characteristics of stiffness and damping vary with frequencies, it is difficult to analyze the dynamic behavior of an engine using general integral algorithms. Convolution integral and relationship between unit impulse response functions and frequency response functions are therefore used to simulate the transient behaviors of an engine indirectly. In time domain, impulse response functions are calculated by two-side discrete inverse courier transform of frequency response function achieved by laplace transform of equations of motion. Considering the fact that the shapes of behavior of an engine simulated by the proposed method are in good agreement with test results, it is confirmed that the proposed method is very effective for the analysis of transient response to throttle tip-in/out of an engine with hydraulic mounts.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.283-288
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• 2002

This paper has shown that the impulse and the unit step responses of 2nd-order systems can be computed by an analytic method. Three different 2nd-order systems are investigated: the prototype system, the system with one LHP(left half plane) real zero and the system with one RHP(right half plane) real zero. It has also shown that the effects of the LHP or the RHP zero are very serious when the zero is getting closer to the origin on the complex plane. Based on these analytic results, this paper has presented two sufficient and necessary conditions for 2nd-order linear SISO(single-input/single-output) stable systems to have the nonovershooting and the monotone nondecreasing step response, respectively. The latter condition can be extended to the sufficient conditions for the monotone nondecreasing step response of high-order systems.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.540-545
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• 2001

In this paper dynamic responses of an engine, which is supported by hydraulic mount, to throttle tip-in/tip out are analyzed. Because the hydraulic mounts have non-linearity which the characteristics of stiffness and damping vary with frequencies, it is difficult to analyze the dynamic behavior of an engine using general integral algorithms. Convolution integrals and relationships between unit impulse response functions and frequency response functions are therefore used to simulate the transient behavior of an engine indirectly. In time domain, impulse response functions are calculated by two-side discrete inverse Fourier transform of frequency response function achieved by Laplace transform of equations of motion. Considering the fact that the shapes of behavior of an engine simulated by the proposed method are in good agreement with test results, it is confirmed that the proposed method is very effective for the analysis of transient response to throttle tip-in/out of an engine with hydraulic mounts.

• The Korean Journal of Applied Statistics
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• v.25 no.2
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• pp.239-249
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• 2012

We estimate nonlinear impulse responses of stock indices by asset class by the Local Projection method as suggested by Jorda (2005) to compute impulse responses. The method estimates impulse responses without the specification and estimation of the underlying multivariate dynamic system unlike the usual way of vector autoregression(VAR). It estimates Local Projections at each period of interest rather than extrapolating into increasingly distant horizons with the advantages of easy estimation and non-linear flexible specification. The Local Projection method adequately captures the nonlinearity and asymmetry of the impulse responses of the stock indices compared to those from VARs.

• Proceedings of the KIEE Conference
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• 1979.08a
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• pp.166-167
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• 1979

Performances of three computational algorithms for one-dimensional frequency filtering are compared and tradeoffs are studied. If the size of the filter impulse response is small, it is well-known that the conventional convolution is superior than the FFT convolution. If the size of the impulse response is large, it was suggested that the recursive filter might be competitive in terms of speed to the FFT convolution. We, therefore, have developed an computational, algorithm for the recursive filter to compare the speed advantages over the FFT convolution and the results are presented.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.980-983
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• 1996

A new version of the discrete-time optimal FIR (finite impulse response) filter utilizing only the measurements of finite sliding estimation window is suggested for linear time-invariant state-space models. This filter is called the BLUFIR (best linear unbiased finite impulse response) filter since it provides the BLUE (best linear unbiased estimate) of the state obtained from the measurements of the estimation window. It is shown that the BLUFIR filter has the deadbeat property when there are no noises in the estimation window.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2548-2551
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• 2005

In this paper, a robust receding horizon finite impulse response(FIR) filter is proposed for a class of linear discrete time systems with uncertainty satisfying an integral quadratic constraint. The robust state estimation problem involves constructing the set of all possible states at the current time consistent with given system input, output measurements and the integral quadratic constraint.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.164-169
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• 1992

Classical methods for estimating transfer function models have not always been successful. A statistic approach to the identification of transfer function models which is corrupted by disturbances or noise is presented. The estimated impulse response is obtained from the autocorrelation function and cross correlation function between the measured input and output. Several data analysis tools such as R- , S- and GPAC array for the estimated impulse response give us pretty clear information on the order of transfer function models.