• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.15 no.6
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• pp.492-498
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• 2002

In this paper, we present the simulation results of multi-layer VCO(voltage controlled oscillator), which is composed of resonator, oscillator, and buffer circuit, using EM simulator and nonlinear RF circuit simulator. EM simulator is used for obtaining the EM(Electromagnetic) characteristics of conductor pattern as well as designing the multi-layer VCO. Obtained EM characteristics were used as real components in nonlinear RF circuit simulation. Finally the overall VCO was simulated by the nonlinear RF circuit simulator. The material for the circuit pattern was Ag and the dielectric was Dupont 951AT, which will be applied for LTCC process. The structure of multi-layer VCO is constructed with 4 conducting layer. Simulated results showed that the output level was about 4.5 [dBm], the phase noise was -104 [dBc/Hz] at 30 [kHz] offset frequency, the harmonics -8 dBc, and the control voltage sensitivity of 30 [MHz/V] with a DC current consumption of 9.5 [mA]. The size of VCO is $6{\times}9{\times}2 mm$(0.11 [cc]).

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.07b
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• pp.653-656
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• 2002

In this paper, we present the simulation results of multi-layer VCO(voltage controlled oscillator), which is composed of resonator, oscillator, and buffer circuit, using EM simulator and nonlinear RF circuit simulator. EM simulator is used for obtaining the EM(Electromagnetic) characteristics of conductor pattern as well as designing the multi-layer VCO. Obtained EM characteristics were used as real components in nonlinear RF circuit simulation. Finally the overall VCO was simulated by the nonlinear RF circuit simulator. The material for the circuit pattern was Ag and the dielectric was DuPont 951AT, which will be applied for LTCC process. The structure of multi-layer VCO is constructed with 4 conducting layer. Simulated results showed that the output level was about 4.5 [dBm], the phase noise was -104 [dBc/Hz] at 30 [kHz] offset frequency, the harmonics -8 dBc, and the control voltage sensitivity of 30 [MHz/V] with a DC current consumption of 9.5 [mA]. The size of VCO is $6{\times}9{\times}2$ mm(0.11[cc]).

• International Journal of Vascular Biomedical Engineering
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• v.3 no.1
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• pp.14-22
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• 2005

In the present study, our aim is to investigate whether responses to the head-up tilt (HUT) on nonlinear properties of heart rate variability (HRV) in young and elderly subjects are different or not. Thirteen young-healthy subjects ($24.5{\pm}3.7$ years) and 18 old-aged healthy subjects ($74.5{\pm}7.4$ years) participated in this study. An electrocardiogram (ECG) in the supine posture, at $0^{\circ}$, and in the standing posture, at $70^{\circ}$ of head-up tilt, was recorded. Detrended fluctuation analysis (DFA) and approximate entropy (ApEn), measures of short-/long-term correlation properties and overall complexity of heart rate (HR) respectively, along with spectral components of HR variability (HRV) were analyzed for both the supine and HUT postures. We observed that the short-term fractal exponent ${\alpha}_1$ increased during HUT posture (F(1, 29) = 39.79, P = 0.000), especially, the young subjects showed a significantly higher values compared to the elderly subjects. ApEn significantly decreased (F(1, 29) = 8.61, P = 0.006) during HUT posture. HUT posture decreased the complexity in HR dynamics and increased short-term fractal exponent values in young subjects but not in elderly subjects. These results imply that there are differences of response to HUT on nonlinear properties between young and elderly subjects.

• Journal of Ocean Engineering and Technology
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• v.12 no.2 s.28
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• pp.33-42
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• 1998

In the presence of incident waves with different frequencies, the second order sum and difference frequency waves due to the nonlinearity of the incident waves come into existence. Although the magnitudes of the forces produced on a Tension Leg Platform(TLP) by these nonlinear waves are small, they act on the TLP at sum and difference frequencies away from those of the incident waves. So, the second order sum and difference frequency wave loads produced close to the natural frequencies of TLPs often give greater contributions to high and low frequency resonant responses. The second order wave exciting forces and moments have been obtained by the method based on direct integration of pressure acting on the submerged surface of a TLP. The components of the second order forces which depend on first order quantities have been evaluated using the three dimensional source distribution method. The numerical results of time domain analysis for the nonlinear wave exciting forces in regular waves are compared with the numerical ones of frequency domain analysis. The results of comparison confirmed the validity of the proposed approach.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.10
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• pp.127-136
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• 2004

This paper is the first of two companion papers concerning the analysis and design of a pneumatic vibration isolation system. The design optimization of the pneumatic vibration isolation system is required for the reduction of cost, endeavor and time, and it needs modeling and calculation algorithm. The nonlinear models are devised from the fluid mechanical expression for components of the system and the calculation algorithm is derived from the mathematical relationship between the models. It is shown that the orifice makes the nonlinear property of the transmissibility curve that the resonant frequency changes by the amplitude of excited vibration. Linearization of the nonlinear models is tried to reduce elapsed time and truncation error accumulation and to enable the transmissibility calculation of the system with multi damping chambers. The equivalent mechanical models generated by linearization clarify the function of each component of the system and lead to the linearized transfer function that can give forth to the transmissibility exactly close to that of nonlinear models. The modified successive under-relaxation method is developed to calculate the linearized transfer function.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.3 s.108
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• pp.263-269
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• 2006

The objective of the present work is to develop a time-domain numerical method of broadband noise in a cascade of airfoils. This paper focuses on dipolar broadband noise sources, resulting from the interaction of turbulent inflows with the flat-plate airfoil cascade. The turbulence response of a two-dimensional cascade is studied by solving both of the linearised and the full nonlinear Euler equations employing accurate higher order spatial differencing, time stepping techniques and non-reflecting inflow/outflow boundary condition. The time-domain result using the linearised Euler equations shows good agreement with the analytical solution using the modified LINSUB code. Through the comparison of the nonlinear time-domain result using the full nonlinear Euler equations with the linear, it is found that the acoustic mode amplitude of the nonlinear response is less than that of the linear response due to the energy cascade from low frequency components to the high frequency ones. Considering the merits of the time-domain methods over the typical time-linearised frequency-domain analysis, the current method is expected to be promising tools for analyzing the effects of the airfoil shapes, non-uniform background flow, linear-nonliear regimes on the broadband noise due to turbulence-cascade interaction.

• International Journal of Control, Automation, and Systems
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• v.2 no.2
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• pp.189-200
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• 2004

In this paper, we introduce a new soft computing technique that dwells on the ideas of combining fuzzy rules in a fuzzy system with polynomial neural networks (PNN). The PNN is a flexible neural architecture whose structure is developed through the modeling process. Unfortunately, the PNN has a fatal drawback in that it cannot be constructed for nonlinear systems with only a small amount of input variables. To overcome this limitation in the conventional PNN, we employed one of three principal soft computing components such as a fuzzy system. As such, a space of input variables is partitioned into several subspaces by the fuzzy system and these subspaces are utilized as new input variables to the PNN architecture. The proposed soft computing technique is achieved by merging the fuzzy system and the PNN into one unified framework. As a result, we can find a workable synergistic environment and the main characteristics of the two modeling techniques are harmonized. Thus, the proposed method alleviates the problems of PNN while providing superb performance. Identification results of the three-input nonlinear static function and nonlinear system with two inputs will be demonstrated to demonstrate the performance of the proposed approach.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.4
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• pp.468-473
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• 2014

This paper describes the in-flight alignment of SDINS (Strapdown Inertial Navigation Systems) using an EKF (Extended Kalman Filter) and a UKF (Unscented Kalam Filter), which allow large initial attitude error uncertainty. Regardless of the inertial sensors, there are nonlinear error dynamics of SDINS in cases of large initial attitude errors. A UKF that is one of the nonlinear filtering approaches for IFA (In-Flight Alignment) are used to estimate the attitude errors. Even though the EKF linearized model makes velocity errors when predicting incorrectly in case of large attitude errors, a UKF can represent correctly the velocity errors variations of attitude errors with nonlinear attitude error components. Simulation results and analyses show that a UKF works well to handle large initial attitude errors of SDINS and the alignment error attitude estimation performance are quite improved.

• Atmosphere
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• v.21 no.3
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• pp.221-228
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• 2011

The nonlinear characteristics of summer monsoon intraseasonal oscillation (ISO) in precipitation, which is manifested as fluctuations in convection and circulation, is one of the major difficulty on the prediction of East Asian summer monsoon (EASM). The present study aims to identify the spatial distribution and time evolution of nonlinear phases of monsoon ISO. In order to classify the different phases of monsoon ISO, Self-Organizing Map(SOM) known as a nonlinear pattern recognition technique is used. SOM has a great attractiveness detecting self-similarity among data elements by grouping and clustering such self-similar components. The four important patterns are demonstrated as Meiyu-Baiu, Changma, post-Changma, and dry-spell modes. It is found that SOM well captured the formation of East Asian monsoon trough during early summer and its northward migration together with enhanced convection over subtropical western Pacific and regionally intensive precipitation including Meiyu, Changma and Baiu. The classification of fundamental large scale spatial pattern and evolutionary history of nonlinear phases of monsoon ISO provides the source of predictability for extended-range forecast of summer precipitation.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1361-1369
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• 2000

For the implementation of 3D Sound Localization system, the binaural filtering by HRTFs is generally employed. But the HRTF filter is of high order and its coefficients for all directions have to be stored, which imposes a rather large memory requirement. To cope with this, research works have centered on obtaining low dimensional HRTF representations without significant loss of information and synthesizing the original HRTF efficiently, by means of feature extraction methods for multivariate dat including PCA. In these researches, conventional linear PCA was applied to the frequency domain HRTF data and using relatively small number of principal components the original HRTFs could be synthesized in approximation. In this paper we applied neural network based nonlinear PCA model (NLPCA) and the nonlinear PLS repression model (NLPLS) for this low dimensional HRTF modeling and analyze the results in comparison with the PCA. The NLPCA that performs projection of data onto the nonlinear surfaces showed the capability of more efficient HRTF feature extraction than linear PCA and the NLPLS regression model that incorporates the direction information in feature extraction yielded more stable results in synthesizing general HRTFs not included in the model training.