• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.6 s.177
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• pp.1593-1600
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• 2000

A method based on frequency domain approaches is presented for the nonlinear parameters identification of structure having nonlinear joints. The finite element model of linear substructure is us ed to calculating its frequency response functions needed in parameter identification process. This method is easily applicable to a complex real structure having nonlinear elements since it uses the frequency response function of finite element model. Since this method is performed in frequency domain, the number of equations required to identify the unknown parameters can be easily increased as many as it needed, just by not only varying excitation amplitude but also selecting excitation frequencies. The validity of this method is tested numerically and experimentally with a cantilever beam having the nonlinear element. It was verified through examples that the method is useful to identify the nonlinear parameters of a structure having arbitary nonlinear boundaries.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.3
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• pp.89-95
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• 2002

This paper describes a new identification method for friction in motion control systems, in which the friction model is not necessarily linear in parameters. The proposed method works well with any measurement data of velocity and input control force, as long as the initial and final velocities are identical. Most importantly, the proposed method does not require the information of acceleration for its implementation, in contrast with the previously known methods. This is due to the orthogonality property between acceleration and a function of velocity. In particular, if the parametric model is linear in parameters, its friction parameters can be identified in closed form without resorting to numerical search methods. To illuminate further the generality and practicality of the proposed friction identification method, we show good performance of the proposed method through some simulation results.

• Speech Sciences
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• v.12 no.2
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• pp.171-182
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• 2005

An efficient GMM (Gaussian mixture modeling) method based on LPCA (local principal component analysis) with VQ (vector quantization) for speaker identification is proposed. To reduce the dimension and correlation of the feature vector, this paper proposes a speaker identification method based on principal component analysis. The proposed method firstly partitions the data space into several disjoint regions by VQ, and then performs PCA in each region. Finally, the GMM for the speaker is obtained from the transformed feature vectors in each region. Compared to the conventional GMM method with diagonal covariance matrix, the proposed method requires less storage and complexity while maintaining the same performance requires less storage and shows faster results.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.276-283
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• 2007

It has been shown that the structure identification of a neuro-fuzzy model improves their accuracy performances in a various modeling problems. In this paper, we claim that the structure identification of a neuro-fuzzy model can also reduce the degree of inconsistency of its fuzzy rulebase. Thus, the resulting neuro-fuzzy model serves as more like a structured knowledge representation scheme. For this, we briefly review a structure identification method of a neuro-fuzzy model and propose a systematic method to measure inconsistency of a fuzzy rulebase. The proposed method is applied to problems or fuzzy system reproduction and nonlinear system modeling in order to validate our claim.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.937-945
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• 2014

Multi-modal biometric system can use another biometric trait in the case of having deficiency at a biometric trait. It also has an advantage of improving the performance of personal identification by using multiple biometric traits, so studies on new biometric traits have continuously been performed. The inner face of finger is a relatively new biometric trait. It has two major features of knuckle lines and wrinkles, which can be used as discriminative features. This paper proposes a finger identification method based on displacement vector to effectively process some variation appeared in contactless hand image. At first, the proposed method produces displacement vectors, which are made by connecting corresponding points acquired by matching each pair of local block. It then recognize finger by measuring the similarity among all the detected displacement vectors. The experimental results using pubic CASIA hand image database show that the proposed method may be effectively applied to personal identification.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.644-646
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• 2004

The closed loop identification(CLID) is a very useful method for on-line applications since it can identify the plant in the closed-loop system composed of the plant and the controller. There are some literatures on CLID, but they and mainly focused on SISO(Single-Input/Single-Output) problem. In this paper, a CLID method is proposed for MIMO(Multi-Input/Multi-Output) systems. The CLID method is applied to a MIMO benchmark plant, TRMS(Twin-Rotor MIMO System). To illustrate the performance of the closed-loop system identification., unit step responses in the TRMS are represented and compared with the open-loop identification via some simulation.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.6
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• pp.559-565
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• 2003

A spectral element model-based structural damage identification method (SDIM) was derived in the previous study by using the damage-induced changes in frequency response functions. However the previous SDIM often provides poor damage identification results because the nonlinear effect of damage magnitude was not taken into account. Thus, this paper improves the previous SDIM by taking into account the nonlinear effect of damage magnitude. Accordingly an iterative solution method is used in this study to solve the nonlinear matrix equation for local damages distribution. The present SDIM is evaluated through the numerically simulated damage identification tests.

• Korean Journal of Pharmacognosy
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• v.39 no.4
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• pp.330-334
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• 2008

Shin Kwae Hwan(神快丸) is a Chinese patent medicine which has been used for polymyositis, trigeminal neuralgiaand ischiodynia in Korea. It consists of 15 kinds of powdered crude drugs. In powered crude drugs, it is hard to identify each component by chemical analysis or morphological examination. However, the method of identification of powdered crude drugs has not been clearly established. For the identification of individual crude drugs in such powdery mixtures, microscopic method may advantageously be used, as it requires only small amount of specimens. In this study, it is demonstrated that the microscopic method is very effective for the identification of 15 crude drug ingredients in Shin Kwae Hwan.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.263-270
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• 2017

Various security threats exist in the smart grid environment due to the fact that information and communication technology are grafted onto an existing power grid. In particular, smart metering data exposes a variety of information such as users' life patterns and devices in use, and thereby serious infringement on personal information may occur. Therefore, we are in a situation where a de-identification algorithm suitable for metering data is required. Hence, this paper proposes a new de-identification method for metering data. The proposed method processes time information and numerical information as de-identification data, respectively, so that pattern information cannot be analyzed by the data. In addition, such a method has an advantage that a query such as a direct range search and aggregation processing in a database can be performed even in a de-identified state for statistical processing and availability.

• 전기의세계
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• v.22 no.4
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• pp.17-24
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• 1973

In the view point of practical engineering the identification problem may be considered as a problem to determine the optimal model in the sense of minimizing a given criterion function using the input-output records of the plant. In the system identification the statistical approach has been known to be very effective when the topological structure of the system and the statistical characteristics of the observation noises are known a priori. But in the practical situation there are many cases when the inforhation about the observation noises or the system noises are not available a priori. Here, the authors propose a new identification method which can be used effectively even in the cases when the variances of observation noises are unknown a priori. In the method, the identification of unknown parameters of a linear diserete system is achieved by minimizing the improved quadratic criterion function which is composed of the term of square equation errors and the term to eliminate the affection of observation noises. The method also gives the estimate of noise variance. Numerical computations for several examples show that the proposed procedure gives satisfactory results even when the short time observation data are provided.