• Journal of Information Processing Systems
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• v.14 no.4
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• pp.807-823
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• 2018

Speaker verification system performance depends on the utterance of each speaker. To verify the speaker, important information has to be captured from the utterance. Nowadays under the constraints of limited data, speaker verification has become a challenging task. The testing and training data are in terms of few seconds in limited data. The feature vectors extracted from single frame size and rate (SFSR) analysis is not sufficient for training and testing speakers in speaker verification. This leads to poor speaker modeling during training and may not provide good decision during testing. The problem is to be resolved by increasing feature vectors of training and testing data to the same duration. For that we are using multiple frame size (MFS), multiple frame rate (MFR), and multiple frame size and rate (MFSR) analysis techniques for speaker verification under limited data condition. These analysis techniques relatively extract more feature vector during training and testing and develop improved modeling and testing for limited data. To demonstrate this we have used mel-frequency cepstral coefficients (MFCC) and linear prediction cepstral coefficients (LPCC) as feature. Gaussian mixture model (GMM) and GMM-universal background model (GMM-UBM) are used for modeling the speaker. The database used is NIST-2003. The experimental results indicate that, improved performance of MFS, MFR, and MFSR analysis radically better compared with SFSR analysis. The experimental results show that LPCC based MFSR analysis perform better compared to other analysis techniques and feature extraction techniques.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.519-522
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• 2006

Accurate modeling of a dynamic system from experimental data is the bases for the model updating or heath monitoring of the system. Modal analysis or modal test is a routine process to get the modal parameters of a dynamic system. The modal parameters include the natural frequencies, damping ratios and mode shapes. This paper presents a new method that can derive the equations of motion for a dynamic system from the modal parameters obtained by the modal analysis or modal test. The present method based on the relation between the eigenvalues and eigenvectors of the state space equation derives the mass, damping and stiffness matrices of the system. The modeling of a cantilevered beam from modal parameters is an example to prove the efficiency and accuracy of the present method. Using the lateral displacements only, not the rotations, gives limited information for the system. The numerical verification up to now gives reasonable results and the verification with the test data is scheduled.

• Speech Sciences
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• v.7 no.1
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• pp.31-37
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• 2000

This paper concerns effective speaker adaptation methods to solve the over-training problem in speaker verification, which frequently occurs when modeling a speaker with sparse training data. While various speaker adaptations have already been applied to speech recognition, these methods have not yet been formally considered in speaker verification. This paper proposes speaker adaptation methods using a combination of MAP and MLLR adaptations, which are successfully used in speech recognition, and applies to speaker verification. Experimental results show that the speaker verification system using a weighted MAP and MLLR adaptation outperforms that of the conventional speaker models without adaptation by a factor of up to 5 times. From these results, we show that the speaker adaptation method achieves significantly better performance even when only small training data is available for speaker verification.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.96-100
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• 1996

So far the analysis and modeling of cutting process is studied commonly assumed as being linear stochastic or chaotic without experimental verification. So we verified force signals of cutting process(ball end-milling) is low-dimensional chaos by calculating Lyapunov Exponents. reconstructing attractor using time delay coordinates and calcula-ting it's fractal dimension.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1103-1120
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• 2015

A self-sensing magnetorheological (MR) damper with embedded piezoelectric force sensor has recently been devised to facilitate real-time close-looped control of structural vibration in a simple and reliable manner. The development and characterization of the self-sensing MR damper are presented based on experimental work, which demonstrates its reliable force sensing and controllable damping capabilities. With the use of experimental data acquired under harmonic loading, a nonparametric dynamic model is formulated to portray the nonlinear behaviors of the self-sensing MR damper based on NARX modeling and neural network techniques. The Bayesian regularization is adopted in the network training procedure to eschew overfitting problem and enhance generalization. Verification results indicate that the developed NARX network model accurately describes the forward dynamics of the self-sensing MR damper and has superior prediction performance and generalization capability over a Bouc-Wen parametric model.

• Composites Research
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• v.15 no.5
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• pp.44-52
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• 2002

To study numerically the mechanical behaviors of advanced composite materials considering the microscopic phenomena as well as the macroscopic properties and behaviors, a multi-scale modeling and analysis by the mathematical homogenization method with the help of the finite element method(FEM) are reviewed. The hierarchical modeling strategy and the formulation are briefly described first to give some idea of the multi-scale framework. The latter half of this article focuses on the verification of the multi-scale analysis by the homogenization method in its applications to real advanced materials. The first example is the verification of the predicted macroscopic(homogenized) properties based on the microstructure of porous ceramics. In spite of the complexity of the random microstructure, the error between the predicted and the measured values was only 1%. Next, two applications to the process simulation of fiber reinforced polymer matrix composites are presented. The permeability characteristics are evaluated for sheared weave fabrics for resin transfer molding(RTM) simulation, and the thermoforming of FRTP sheet is analyzed considering the large deformation of the knit structure during the deep-draw forming was verified by comparison with the experimental results.

• Proceedings of the KIPE Conference
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• 2017.07a
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• pp.365-366
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• 2017

LLC resonant DC-DC converter is widely used in many kinds of applications such as battery energy storage systems, wireless power transfer and high voltage power supply. It is because of characteristics like high efficiency, power density, isolation, wide power level and stability enhancement at high switching frequency. Small signal modeling helps to design controller of the converter by approximating the behavior of nonlinear system with linear state equations. This paper presents comparison between small signal modeling analysis and experimental results of LLC resonant converter.

• Journal of Biosystems Engineering
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• v.14 no.3
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• pp.151-157
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• 1989

A mathematical model was developed to predict traction forces of rigid wheels. The modeling was based on the energy principle that the total energy delivered to a driving wheel is equal to the works done by the useful traction force and motion resistance of that wheel. The effect of the wheel slippage was also included in the modeling. Verification of the proposed model was provided by comparing the tractive coefficients predicted by the model to those obtained experimentally at the in-door soil bin tests. The model predictions were found to be a reasonable agreement with the experimental results.

• Journal of Mechanical Science and Technology
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• v.16 no.3
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• pp.310-319
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• 2002

This paper deals with the analytical modeling, and the experimental verification of the strain rate self-sensing method using a hybrid adaptive filter for a cantilevered piezoelectric beam. The piezoelectric beam consists of two laminated lead zirconium titanates (PZT) on a metal shim. A mathematical model of the beam dynamics is derived by Hamilton's principle and the accuracy of the modeling is verified through the comparison with experimental results. For the strain rate estimation of the cantilevered piezoelectric beam, a self-sensing mechanism using a hybrid adaptive filter is considered. The discrete parts of this mechanism are realized by the DS1103 DSP board manufactured by dSPACE$\^$TM/. The efficacy of this method is investigated through the comparison of experimental results with the predictions from the derived analytical model.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.170.2-170
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• 2001

In this paper, the dynamic system modeling and the state sensitivity analysis of the spin-coater system for the reduction of the vibration are proposed. In the respect of modeling, the spin-coater system is composed of components of servomotor, belt, spindle, and a supported base. Each component is defined and combined modeling is derived to 3dimensional equations. Verification of modeling is verified by experimental values of actual system in the frequency domain. By direct differentiation the constraint equations with respect to kinematic design variables, such as eccentricity of spindle, moment of inertia, torsional stiffness and damping of supported base, sensitivity equations are derived to the verified state equations. Sensitivity of design variables could be used for vibration reduction and natural frequency shift in the frequency domain. Finally, dominant design variables ...