• 제목/요약/키워드: nonlinear algorithm

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NSG : 비선형 알고리즘을 이용한 블루투스 E0 암호화시스템의 성능 개선 (NSG : A Security Enhancement of the E0 Cipher Using Nonlinear Algorithm in Bluetooth System)

  • 김형락;이훈재;문상재
    • 정보처리학회논문지C
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    • 제16C권3호
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    • pp.357-362
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    • 2009
  • 합산수열 발생기는 간단한 하드웨어 또는 소프트웨어로 구현될 수 있고, 주기와 선형복잡도가 높은 특징이 있어 유비쿼터스 시대의 이동환경 보안장치에 적합하다. 하지만 Golic의 상관성공격과 Meier의 고속 상관성공격에 의해 취약성이 노출되었다. 본 논문에서는 합산 수열 발생기 형태의 $E_0$ 알고리즘에서 LFSR과 비선형 귀환 이동 레지스터 NFSR(nonlinear feedback shift register) 를 조합한 형태로 개선하여 비선형성을 높이고, 상관성 공격 등의 암호해독이 어려운 새로운 알고리즘 NSG를 제안하고, 제안 알고리즘에 대하여 안전성 및 성능을 분석하였다.

Nonlinear Regression with Censored Data

  • Shin, D.W.;Bai, D.S.
    • Journal of the Korean Statistical Society
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    • 제12권1호
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    • pp.46-56
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    • 1983
  • An algorithm based on EM procedure which finds maximum likelihood estimators in a nonlinear regression with censored data is proposed, and asymptotic properties of the estimator are investigated in detail. Some numerical examples are also given.

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유전자 알고리즘을 이용한 비선형 흡착 식 및 이류-확산 모델 파라미터 추정 (Estimation of Nonlinear Adsorption Isotherms and Advection-Dispersion Model Parameters Using Genetic Algorithm)

  • 도남영;이승래;박현일
    • 한국지반환경공학회 논문집
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    • 제7권1호
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    • pp.41-53
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    • 2006
  • 본 연구에서는 아연 및 카드뮴을 대상으로 수행된 흡착실험과 칼럼확산실험 결과를 바탕으로 유전자 알고리즘을 이용한 최적화 과정을 통하여 비선형 흡착 모델 및 이류-확산 모델식의 파라미터들을 추정하여 보았다. 수행결과 비선형 흡착 식 (Langmuir 흡착모델과 Freundlich 흡착모델) 들의 모델파라미터 추정은 이들 흡착식 들의 선형화 과정을 거쳐 얻어진 파라미터들과 거의 일치하는 결과를 얻을 수 있었다. 오염물질의 이동 해석을 위해 수행된 이류-확산 모델의 유한요소해석과 모델 파라미터 추정을 위해 수행된 최적화 과정을 통해 얻은 아연과 카드뮴의 확산계수는 선형 분배계수를 이용할 경우 두 금속 모두에서 약 $10^{-7}cm^2/s$ 차원의 확산계수를 얻을 수 있었다. 또한 비선형 흡착 모델로부터 얻어진 지연인자를 이용할 경우 두 금속 모두에서 $10^{-6}{\sim}10^{-5}cm^2/s$ 범위의 확산계수 값을 얻을 수 있었다. 결론적으로 유전자 알고리즘을 이용한 최적화 과정을 통한 비선형 흡착식 및 이류-확산 모델의 파라미터 추정은 성공적으로 수행될 수 있었고, 실측값과 최적화 과정을 거쳐 예측된 값 사이의 상관계수는 0.9 이상으로 높은 상관성을 보이는 것으로 나타났다.

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Optimal nonlinear Parameter Estimation of Steady-State Induction Motor using Immune Algorithm

  • Kim, Dong-Hwa;Cho, Jae-Hoon;Hong, Won-Pyo;Lee, Seung-Hack;Lee, Hwan
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.891-895
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    • 2004
  • This paper suggests the techniques in determining the values of the steady-state equivalent circuit parameters of a three-phase squirrel-cage induction machine using immune algorithm. The parameter estimation procedure is based on the steady state phase current versus slip and input power versus slip characteristics. The proposed estimation algorithm is of a nonlinear kind based on clonal selection in immune algorithm. The machine parameters are obtained as the solution of a minimization of least-squares cost function by immune algorithm. Simulation shows better results than the conventional approaches.

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변분법을 이용한 재귀신경망의 온라인 학습 (A on-line learning algorithm for recurrent neural networks using variational method)

  • 오원근;서병설
    • 제어로봇시스템학회논문지
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    • 제2권1호
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    • pp.21-25
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    • 1996
  • In this paper we suggest a general purpose RNN training algorithm which is derived on the optimal control concepts and variational methods. First, learning is regared as an optimal control problem, then using the variational methods we obtain optimal weights which are given by a two-point boundary-value problem. Finally, the modified gradient descent algorithm is applied to RNN for on-line training. This algorithm is intended to be used on learning complex dynamic mappings between time varing I/O data. It is useful for nonlinear control, identification, and signal processing application of RNN because its storage requirement is not high and on-line learning is possible. Simulation results for a nonlinear plant identification are illustrated.

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퍼지 로직 알고리듬을 이용한 차량 구동력 제어 (Vehicle traction control using fuzzy logic algorithm)

  • 박성훈;권동수
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.680-683
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    • 1996
  • The dynamics of the vehicle system has highly nonlinear components such as an engine, a torque converter and variable road condition. This thesis proposes a Fuzzy Logic Algorithm that shows better control performance than Antiwindup PI in the highly nonlinear vehicle system. Traction Control System(TCS), which adjusts throttle valve opening by Fuzzy Logic Algorithm improves vehicle drivability, steerability and stability when vehicle is starting and cornering. When a throttle valve is opened at large degree, Fuzzy Logic Algorithm shows better performances like a small settling time and a small oscillation than Antiwindup PI in simulation. The decreased desired slip ratio improves steerability in the simulation when a vehicle is cornering. The Fuzzy Logic Algorithm has been tested by a 1/5-scale vehicle for tracking the constant desired velocity.

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적응 FWLS 알고리즘을 응용한 시변 비선형 시스템 식별 (Utilization of the Filtered Weighted Least Squares Algorithm For the Adaptive Identification of Time-Varying Nonlinear Systems)

  • 안규영;이인환;남상원
    • 대한전기학회논문지:시스템및제어부문D
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    • 제53권12호
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    • pp.793-798
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    • 2004
  • In this paper, the problem of adaptively identifying time-varying nonlinear systems is considered. For that purpose, the discrete time-varying Volterra series is employed as a system model, and the filtered weighted least squares (FWLS) algorithm, developed for adaptive identification of linear time-varying systems, is utilized for the adaptive identification of time-varying quadratic Volterra systems. To demonstrate the performance of the proposed approach, some simulation results are provided. Note that the FWLS algorithm, decomposing the conventional weighted basis function (WBF) algorithm into a cascade of two (i.e., estimation and filtering) procedures, leads to fast parameter tracking with low computational burden, and the proposed approach can be easily extended to the adaptive identification of time-varying higher-order Volterra systems.

Design of an Adaptive Nonlinear Compensator using a Wavelet Transform Domain Volterra Filter and a Modified Escalator Algorithm

  • Hwang, Dong-Oh;Kang, Dong-Jun;Nam, Sang-Won
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.98.5-98
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    • 2001
  • An efficient adaptive nonlinear compensator, based on a wavelet transform domain adaptive Volterra filter along with a modified escalator algorithm, is proposed to speed up the convergence rate of an adaptive LMS algorithm. In particular, it is well known that the e.g., slow convergence speed of an adaptive LMS algorithm depends on the statistical characteristics (e.g., large eigenvalue spread) of the corresponding auto-correlation matrix of the input vector. To solve such a convergence problem, the proposed approach utilizes a modified escalator algorithm and a wavelet transform domain adaptive LMS Volterra filtering technique, which leads to diagonalization of the auto-correlation matrix of the ...

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Optimal Design of a Squeeze Film Damper Using an Enhanced Genetic Algorithm

  • Ahn, Young-Kong;Kim, Young-Chan;Yang, Bo-Suk
    • Journal of Mechanical Science and Technology
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    • 제17권12호
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    • pp.1938-1948
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    • 2003
  • This paper represents that an enhanced genetic algorithm (EGA) is applied to optimal design of a squeeze film damper (SFD) to minimize the maximum transmitted load between the bearing and foundation in the operational speed range. A general genetic algorithm (GA) is well known as a useful global optimization technique for complex and nonlinear optimization problems. The EGA consists of the GA to optimize multi-modal functions and the simplex method to search intensively the candidate solutions by the GA for optimal solutions. The performance of the EGA with a benchmark function is compared to them by the IGA (Immune-Genetic Algorithm) and SQP (Sequential Quadratic Programming). The radius, length and radial clearance of the SFD are defined as the design parameters. The objective function is the minimization of a maximum transmitted load of a flexible rotor system with the nonlinear SFDs in the operating speed range. The effectiveness of the EGA for the optimal design of the SFD is discussed from a numerical example.

적응 문턱치 알고리즘을 이용한 충격잡음 제거 (Impulse Noise Cancellation Using Adaptive Threshold Algorithm)

  • 이진;박종환;김세동;이영석;김성환
    • 한국음향학회지
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    • 제19권8호
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    • pp.26-34
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    • 2000
  • This paper presents a new adaptive impulse noise cancelling technique based on the adaptive nonlinear suppressing function. The proposed "adaptive threshold algorithm (ATA)" is controlled by the normalized power prior input data term, and this adaptive threshold makes the cancelling system highly robust against additive impulse noise. For the performance evaluation, we have tested the proposed algorithm with the observed signals simulated in various impulsive noise environments and real EMG signals. As a result the proposed algorithm shows superior performance of 51.7% to the available techniques in the points of SNR and MSE.

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