• Title/Summary/Keyword: parameter analysis

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Features for Figure Speech Recognition in Noise Environment (잡음환경에서의 숫자음 인식을 위한 특징파라메타)

  • Lee, Jae-Ki;Koh, Si-Young;Lee, Kwang-Suk;Hur, Kang-In
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.2
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    • pp.473-476
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    • 2005
  • This paper is proposed a robust various feature parameters in noise. Feature parameter MFCC(Mel Frequency Cepstral Coefficient) used in conventional speech recognition shows good performance. But, parameter transformed feature space that uses PCA(Principal Component Analysis)and ICA(Independent Component Analysis) that is algorithm transformed parameter MFCC's feature space that use in old for more robust performance in noise is compared with the conventional parameter MFCC's performance. The result shows more superior performance than parameter and MFCC that feature parameter transformed by the result ICA is transformed by PCA.

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Determination and Analysis of Signal-to-Noise Ratios for Parameter Design with Dynamic Characteristics (동특성 파라미터설계를 위한 SN비의 결정 및 분석)

  • 김성준
    • Journal of Korean Society for Quality Management
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    • v.26 no.2
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    • pp.17-26
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    • 1998
  • Taguchi's parameter design is a method for quality improvement by making the performance fo a system robust to noise. Parameter design with dynamic characteristics has been recently the subject of much interest. This paper is concerned with a review and a generalization of the Signal-to-Noise (SN) ratio, a quality measure for parameter design with dynamic characteristics, proposed by Taguchi. We present a method for determination and analysis of the generalized SN ratio and illustrate its implementation by example.

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Comparison of Rotor Flux Observer Characteristics in Induction Motor Using Parameter Sensitivity (파라미터 민감도를 이용한 유도전동기 회전자 자속관측기의 특성 비교)

  • 최종우;남현택;박용환;김흥근
    • The Transactions of the Korean Institute of Power Electronics
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    • v.7 no.4
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    • pp.377-383
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    • 2002
  • To obtain a high performance in a direct vector controlled induction machine, it is essential to obtain the current rotor flux. The accuracy of flux observers for induction machines inherently depends on parameter sensitivity. This paper proposes an analysis method for conventional flux observers using "parameter sensitivity". The "parameter sensitivity" is defined as the ratio of the percentage change in the system transfer function to the percentage change of the parameter variation. We define the ratio between real flux and estimated no as the transfer function, and analyze a parameter sensitivity of this transfer function. Practical verification is presented to conform the capabilities of the proposed analysis method.sed analysis method.

Vibration analysis of porous nanocomposite viscoelastic plate reinforced by FG-SWCNTs based on a nonlocal strain gradient theory

  • Khazaei, Pegah;Mohammadimehr, Mehdi
    • Computers and Concrete
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    • v.26 no.1
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    • pp.31-52
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    • 2020
  • This paper investigates the size dependent effect on the vibration analysis of a porous nanocomposite viscoelastic plate reinforced by functionally graded-single walled carbon nanotubes (FG-SWCNTs) by considering nonlocal strain gradient theory. Therefore, using energy method and Hamilton's principle, the equations of motion are derived. In this article, the effects of nonlocal parameter, aspect ratio, strain gradient parameter, volume fraction of carbon nanotubes (CNTs), damping coefficient, porosity coefficient, and temperature change on the natural frequency are perused. The innovation of this paper is to compare the effectiveness of each mentioned parameters individually on the free vibrations of this plate and to represent the appropriate value for each parameter to achieve an ideal nanocomposite plate that minimizes vibration. The results are verified with those referenced in the paper. The results illustrate that the effect of damping coefficient on the increase of natural frequency is significantly higher than the other parameters effect, and the effects of the strain gradient parameter and nonlocal parameter on the natural frequency increase are less than damping coefficient effect, respectively. Furthermore, the results indicate that the natural frequency decreases with a rise in the nonlocal parameter, aspect ratio and temperature change. Also, the natural frequency increases with a rise in the strain gradient parameter and CNTs volume fraction. This study can be used for optimizing the industrial and medical designs, such as automotive industry, aerospace engineering and water purification system, by considering ideal properties for the nanocomposite plate.

Parameter Study of Roller Leveling Process of Steel Cord Using Finite Element Analysis (유한요소해석을 이용한 스틸코드 롤러교정공정의 영향인자 분석)

  • Bae, G.H.;Lee, J.S.;Huh, H.;Lee, J.W.
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • 2008.10a
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    • pp.245-248
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    • 2008
  • This paper deals with the parameter study of roller leveling process of steel cord using finite element analysis. A simplified model of roller leveling process is constructed for the efficient numerical simulation considering the computing time. Using the constructed simulation scheme, the parameter study of main process parameters, such as back-tension and intermesh, is carried out in order to evaluate elastic recovery angle and roller force quantitatively. The effect of the initial shape of steel cord is also evaluated during the parameter study. And the mechanism of roller leveling process is verified by investigating the residual stress distribution.

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Study on the Prediction Technique of Vehicle Performance using Parameter Analysis (파라미터 해석을 통한 차량 성능 예측 기법 연구)

  • Kim, Ki-Chang;Kim, Chan-Mook;Kim, Jin-Taek
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2009.10a
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    • pp.647-653
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    • 2009
  • Taguchi parameter design is an approach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used SN (Signal to Noise) ratio to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. This paper describes the prediction technique of vehicle performance using parameter analysis to reduce man hour and test development period as well as to achieve stable NVH performance. Design engineer could efficiently decide the design variable using parameter analysis database in early design stage. These improvements can reduce the time needed to develop better vehicles.

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Robust adaptive control by single parameter adaptation and the stability analysis (단일계수적응을 통한 강건한 적응제어시의 설계및 안정성 해석)

  • 오준호
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.14 no.2
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    • pp.331-338
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    • 1990
  • In adaptive control, the lack of persistent and rich excitation causes the estimated parameters to drift, which degrade the performance of the system and may introduces instability to the system in a stochastic environment. To solve the problem of the parameter drift, the concept of single parameter adaptation is presented. For the parameter identification, a priori error is directly used for adaptation error. The structure of the controller is based upon the minimum variance control technique. The stability and robustness analysis is carried out by the sector stability theorem for the second order system. The computer simulation is performed to justify the theoretical analysis for the various cases.

Regression analysis and recursive identification of the regression model with unknown operational parameter variables, and its application to sequential design

  • Huang, Zhaoqing;Yang, Shiqiong;Sagara, Setsuo
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10b
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    • pp.1204-1209
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    • 1990
  • This paper offers the theory and method for regression analysis of the regression model with operational parameter variables based on the fundamentals of mathematical statistics. Regression coefficients are usually constants related to the problem of regression analysis. This paper considers that regression coefficients are not constants but the functions of some operational parameter variables. This is a kind of method of two-step fitting regression model. The second part of this paper considers the experimental step numbers as recursive variables, the recursive identification with unknown operational parameter variables, which includes two recursive variables, is deduced. Then the optimization and the recursive identification are combined to obtain the sequential experiment optimum design with operational parameter variables. This paper also offers a fast recursive algorithm for a large number of sequential experiments.

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A Generalized Modal Analysis for Multi-Stepped, Distributed-Parameter Rotor-Bearing Systems (다단 연속 회전체 베어링 계의 일반화된 모드 해석)

  • 박종혁;홍성욱
    • Journal of KSNVE
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    • v.9 no.3
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    • pp.525-534
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    • 1999
  • The present paper proposes a generalized modal analysis procedure for non-uniform, distributed-parameter rotor-bearing systems. An exact element matrix is derived for a Timoshenko shaft model which contains rotary inertia, shear deformation, gyroscopic effect and internal damping. Complex coordinates system is adopted for the convenience in formulation. A generalized orthogonality condition is provided to make the modal decomposition possible. The generalized modal analysis by using a modal decomposition delivers exact and closed form solutions both for frequency and time responses. Two numerical examples are presented for illustrating the proposed method. The numerical study proves that the proposed method is very efficient and useful for the analysis of distributed-parameter rotor-bearing systems.

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Change point analysis in Bitcoin return series : a robust approach

  • Song, Junmo;Kang, Jiwon
    • Communications for Statistical Applications and Methods
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    • v.28 no.5
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    • pp.511-520
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    • 2021
  • Over the last decade, Bitcoin has attracted a great deal of public interest and Bitcoin market has grown rapidly. One of the main characteristics of the market is that it often undergoes some events or incidents that cause outlying observations. To obtain reliable results in the statistical analysis of Bitcoin data, these outlying observations need to be carefully treated. In this study, we are interested in change point analysis for Bitcoin return series having such outlying observations. Since these outlying observations can affect change point analysis undesirably, we use a robust test for parameter change to locate change points. We report some significant change points that are not detected by the existing tests and demonstrate that the model allowing for parameter changes is better fitted to the data. Finally, we show that the model with parameter change can improve the forecasting performance of Value-at-Risk.