• Title/Summary/Keyword: identification function

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Jammer Identification: Spectral Correlation Function and Wavelet Coherence

  • Jin, Mi Hyun;Choi, Yun Sub;Choi, Heon Ho;Lee, Sang Jeong
    • Journal of Positioning, Navigation, and Timing
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    • v.7 no.3
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    • pp.147-153
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    • 2018
  • Jamming countermeasures are used to decrease or prevent the impact of intentional jamming applied to degrade the quality of information provided by a global navigation satellite system (GNSS) receiver. The maximum performance of jamming countermeasure can be obtained only when a proper technique is applied according to the type of jammer. This paper suggests a jamming identification technique for providing information regarding the type of jamming. The center frequency and bandwidth of jammer signal are inconsistent and may change according to time, and thus a spectral correlation function and wavelet coherence were considered in order to analyze the signal in the time and frequency space. Because the two characteristics derive different analysis results, two different identification techniques were suggested and the performances thereof were analyzed. Numerical results show that the two identification techniques have relative advantages and disadvantages as to time consumed and performance. The suggested methods can sufficiently identify the jammer before the GNSS receiver becomes inoperable because of jamming.

A Feasibility Study on the Application of the Topology Optimization Method for Structural Damage Identification (구조물의 결함 규명을 위한 위상최적설계 기법의 적용가능성 연구)

  • Lee, Joong-Seok;Kim, Jae-Eun;Kim, Yoon-Young
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.16 no.2 s.107
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    • pp.115-123
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    • 2006
  • A feasibility of using the topology optimization method for structural damage identification is investigated for the first time. The frequency response functions (FRFs) are assumed to be constructed by the finite element models of damaged and undamaged structures. In addition to commonly used resonances, antiresonances are employed as the damage identifying modal parameters. For the topology optimization formulation, the modal parameters of the undamaged structure are made to approach those of the damaged structure by means of the constraint equations, while the objective function is an explicit penalty function requiring clear black-and-white images. The developed formulation is especially suitable for damage identification problems dealing with many modal parameters. Although relatively simple numerical problems were considered in this investigation, the possibility of using the topology optimization method for structural damage identification is suggested through this research.

A Structural Damage Identification Method Based on Spectral Element Model and Frequency Response Function

  • Lee, U-Sik;Min, Seung-Gyu;Kwon, Oh-Yang
    • 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.

A Study On Identification Of A Linear Discrete System When The Statistical Characteristics Of Observation Noise Are Unknown (측정잡음의 통계적 성질이 미지인 경우의 선형 이산치형계통의 동정에 관한 연구)

  • 하주식;박장춘
    • 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.

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System Identification of Flexible beam Using Eigensystem Realization Algorithm (Eigensystem Realization Algorithm을 이용한 유연한 빔의 운동방정식 규명)

  • Lee, In-Sung;Lee, Jae-Won;Lee, Soo-Cheol
    • Proceedings of the KSME Conference
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    • 2000.04a
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    • pp.566-572
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    • 2000
  • The System identification is the process of developing or improving a mathematical model of a physical system using experimental data of the input, output and noise relationship. The field of system identification has been an important discipline within the automatic control area. The reason is the requirement that mathematical models having a specified accuracy must be used to apply modem control methods. In this paper, it is confirmed that we can obtain transfer function of flexible beam that is expressed in the forms of identified state-space system matrix A, B, C, D and identified observer gain G using Eigensystem Realization Algorithm including singular value decomposition. And these matrices can be applied to the automatic control. In addition to, it is also confirmed that transfer function can express a system using identified observer gain G, in spite of a noisy data or a periodic disturbance.

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Identification of Damages within a Plate Structure (평판 구조물의 손상규명)

  • Kim, Nam-In;Lee, U-Sik
    • Proceedings of the KSME Conference
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    • 2000.11a
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    • pp.671-675
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    • 2000
  • In this study, an FRF-based structural damage identification method (SDIM) is proposed for plate structures. The present SDIM is derived from the partial differential equation of motion of the damaged plate, in which damage is characterized by damage distribution function. Various factors that might affect the accuracy of the damage identification are investigated. They include the number of modal data used in the analysis and the damage-induced modal coupling. In the present SDIM, an efficient iterative damage self-search method is introduced. The iterative damage search method efficiently reduces the size of problem by searching out and then by removing all damage-free zones at each iteration of damage identification analysis. The feasibility of the present SDIM is studied by some numerically simulated tests.

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A developed hybrid method for crack identification of beams

  • Vosoughi, Ali.R.
    • Smart Structures and Systems
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    • v.16 no.3
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    • pp.401-414
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    • 2015
  • A developed hybrid method for crack identification of beams is presented. Based on the Euler-Bernouli beam theory and concepts of fracture mechanics, governing equation of the cracked beams is reformulated. Finite element (FE) method as a powerful numerical tool is used to discritize the equation in space domain. After transferring the equations from time domain to frequency domain, frequencies and mode shapes of the beam are obtained. Efficiency of the governed equation for free vibration analysis of the beams is shown by comparing the results with those available in literature and via ANSYS software. The used equation yields to move the influence of cracks from the stiffness matrix to the mass matrix. For crack identification measured data are produced by applying random error to the calculated frequencies and mode shapes. An objective function is prepared as root mean square error between measured and calculated data. To minimize the function, hybrid genetic algorithms (GAs) and particle swarm optimization (PSO) technique is introduced. Efficiency, Robustness, applicability and usefulness of the mixed optimization numerical tool in conjunction with the finite element method for identification of cracks locations and depths are shown via solving different examples.

Reducing RFID Reader Load with the Meet-in-the-Middle Strategy

  • Cheon, Jung-Hee;Hong, Jeong-Dae;Tsudik, Gene
    • Journal of Communications and Networks
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    • v.14 no.1
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    • pp.10-14
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    • 2012
  • When tag privacy is required in radio frequency identification (ID) system, a reader needs to identify, and optionally authenticate, a multitude of tags without revealing their IDs. One approach for identification with lightweight tags is that each tag performs pseudo-random function with his unique embedded key. In this case, a reader (or a back-end server) needs to perform a brute-force search for each tag-reader interaction, whose cost gets larger when the number of tags increases. In this paper, we suggest a simple and efficient identification technique that reduces readers computation to $O$(${\sqrt{N}}$ log$N$) without increasing communication cost. Our technique is based on the well-known "meet-in-the-middle" strategy used in the past to attack symmetric ciphers.

Design of Fuzzy-Neural Networks Structure using Optimization Algorithm and an Aggregate Weighted Performance Index (최적 알고리즘과 합성 성능지수에 의한 퍼지-뉴럴네트워크구조의 설계)

  • Yoon, Ki-Chan;Oh, Sung-Kwun;Park, Jong-Jin
    • Proceedings of the KIEE Conference
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    • 1999.07g
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    • pp.2911-2913
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    • 1999
  • This paper suggest an optimal identification method to complex and nonlinear system modeling that is based on Fuzzy-Neural Network(FNN). The FNN modeling implements parameter identification using HCM algorithm and optimal identification algorithm structure combined with two types of optimization theories for nonlinear systems, we use a HCM Clustering Algorithm to find initial parameters of membership function. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using optimal identification algorithm. The proposed optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregate objective function(performance index) with weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.

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Hydrologic Time Series Model by Transfer Function (대체함수에 의한 수문 시계열 모형)

  • 강관원;김주환
    • Water for future
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    • v.24 no.3
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    • pp.61-70
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    • 1991
  • the relationships between rainfall and runoff are analyzed statistically and modelled using discrete linear transfer function, which can be shown with the relations between input and output in hydrologic system. The procedures of identification, estimation and diagnostic checking of model are proposed, and the suitabilith of assume model is determined by the statistics used in time series analysis.

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