• Title/Summary/Keyword: Robust Filter

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FIR Filter for Defense Mechanism against Malicious Cyber Attacks (악의적 사이버 공격을 무력화하기 위한 FIR 필터에 관한 연구)

  • Lee, Sang-Su;Kim, Kwan-Soo;Kang, Hyun-Ho;You, Sung-Hyun;Lee, Dhong-Hun;Lee, Dong-Kyu;Kim, Young-Eun;Ahn, Choon-Ki
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.10a
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    • pp.438-441
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    • 2018
  • In this paper, we propose a finite impulse response (FIR) filter under malicious cyber attacks. The FIR filter shows the robust performance against the malicious cyber attacks. The Kalman filter (KF), one of the widely used filters, is introduced as a comparison of robust performance of the proposed method. The robust performance of the proposed method under malicious cyber attacks is demonstrated through experimental results.

Specified Object Tracking Problem in an Environment of Multiple Moving Objects

  • Park, Seung-Min;Park, Jun-Heong;Kim, Hyung-Bok;Sim, Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.11 no.2
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    • pp.118-123
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    • 2011
  • Video based object tracking normally deals with non-stationary image streams that change over time. Robust and real time moving object tracking is considered to be a problematic issue in computer vision. Multiple object tracking has many practical applications in scene analysis for automated surveillance. In this paper, we introduce a specified object tracking based particle filter used in an environment of multiple moving objects. A differential image region based tracking method for the detection of multiple moving objects is used. In order to ensure accurate object detection in an unconstrained environment, a background image update method is used. In addition, there exist problems in tracking a particular object through a video sequence, which cannot rely only on image processing techniques. For this, a probabilistic framework is used. Our proposed particle filter has been proved to be robust in dealing with nonlinear and non-Gaussian problems. The particle filter provides a robust object tracking framework under ambiguity conditions and greatly improves the estimation accuracy for complicated tracking problems.

Hybrid Adaptive Volterra Filter Robust to Nonlinear Distortion

  • Kwon, Oh-Sang
    • The Journal of the Acoustical Society of Korea
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    • v.27 no.3E
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    • pp.95-103
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    • 2008
  • In this paper, the new hybrid adaptive Volterra filter was proposed to be applied for compensating the nonlinear distortion of memoryless nonlinear systems with saturation characteristics. Through computer simulations as well as the analytical analysis, it could be shown that it is possible for both conventional Volterra filter and proposed hybrid Volterra filter, to be applied for linearizing the memoryless nonlinear system with nonlinear distortion. Also, the simulations results demonstrated that the proposed hybrid filter may have faster convergence speed and better capability of compensating the nonlinear distortion than the conventional Volterra filter.

A Robust Crack Filter Based on Local Gray Level Variation and Multiscale Analysis for Automatic Crack Detection in X-ray Images

  • Peng, Shao-Hu;Nam, Hyun-Do
    • Journal of Electrical Engineering and Technology
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    • v.11 no.4
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    • pp.1035-1041
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    • 2016
  • Internal cracks in products are invisible and can lead to fatal crashes or damage. Since X-rays can penetrate materials and be attenuated according to the material’s thickness and density, they have rapidly become the accepted technology for non-destructive inspection of internal cracks. This paper presents a robust crack filter based on local gray level variation and multiscale analysis for automatic detection of cracks in X-ray images. The proposed filter takes advantage of the image gray level and its local variations to detect cracks in the X-ray image. To overcome the problems of image noise and the non-uniform intensity of the X-ray image, a new method of estimating the local gray level variation is proposed in this paper. In order to detect various sizes of crack, this paper proposes using different neighboring distances to construct an image pyramid for multiscale analysis. By use of local gray level variation and multiscale analysis, the proposed crack filter is able to detect cracks of various sizes in X-ray images while contending with the problems of noise and non-uniform intensity. Experimental results show that the proposed crack filter outperforms the Gaussian model based crack filter and the LBP model based method in terms of detection accuracy, false detection ratio and processing speed.

Filtering of Filter-Bank Energies for Robust Speech Recognition

  • Jung, Ho-Young
    • ETRI Journal
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    • v.26 no.3
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    • pp.273-276
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    • 2004
  • We propose a novel feature processing technique which can provide a cepstral liftering effect in the log-spectral domain. Cepstral liftering aims at the equalization of variance of cepstral coefficients for the distance-based speech recognizer, and as a result, provides the robustness for additive noise and speaker variability. However, in the popular hidden Markov model based framework, cepstral liftering has no effect in recognition performance. We derive a filtering method in log-spectral domain corresponding to the cepstral liftering. The proposed method performs a high-pass filtering based on the decorrelation of filter-bank energies. We show that in noisy speech recognition, the proposed method reduces the error rate by 52.7% to conventional feature.

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Robust 2 D.O.F. Controller for the Precesses with dead-time (시간지연을 갖는 프로세서의 견실한 2자유도 제어기)

  • 최주용;배종일;이만형
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.319-319
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    • 2000
  • In this paper, A dead-time compensator (DTC) for the processes with long dead-time is proposed. The processes which consist of dead-time, time-constant, gain are estimated by the linear least squares method in the frequency domain. A Smith predictor(SP) modified by including a filter becomes a two degree of freedom DTC. So the proposed DTC can yield the desirable setpoint and load disturbance responses separately. PI controller is used for the primary controller and the filter is tuned to be robust. Simulation examples demonstrate the properties of the proposed DTC.

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Extraction of Facial Region Using Fuzzy Color Filter (퍼지 색상 필터를 이용한 얼굴 영역 추출)

  • Kim, M.H.;Park, J.B.;Jung, K.H.;Joo, Y.H.;Lee, J.;Cho, Y.J.
    • Proceedings of the KIEE Conference
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    • 2004.11c
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    • pp.147-149
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    • 2004
  • There are no authentic solutions in a face region extraction problem though it is an important part of pattern recognition and has diverse application fields. It is not easy to develop the facial region extraction algorithm because the facial image is very sensitive according to age, sex, and illumination. In this paper, to solve these difficulties, a fuzzy color filer based on the facial region extraction algorithm is proposed. The fuzzy color filter makes the robust facial region extraction enable by modeling the skin color. Especially, it is robust in facial region extraction with various illuminations. In addition, to identify the fuzzy color filter, a linear matrix inequality(LMI) optimization method is used. Finally, the simulation result is given to confirm the superiority of the proposed algorithm.

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The Motion Estimation of Caterpilla-type Mobile Robot Using Robust SLAM (강인한 SLAM을 이용한 무한궤도형 이동로봇의 모션 추정)

  • Byun, Sung-Jae;Lee, Suk-Gyu;Park, Ju-Hyun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.4
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    • pp.817-823
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    • 2009
  • This paper proposes a robust method for mapping of a caterpillar-type mobile robot which inherently has uncertainty in its modeling by compensating for the estimated pose error of the robot. In general, a caterpillar type robot is difficult to model, which results in inaccuracy in Simultaneous Localization And Mapping(SLAM). To enhance the robustness of the SLAM for a caterpillar-type mobile robot, we factorize the SLAM posterior, where we used particle filter to estimate the position of the robot and Extended Kalman Filter(EKF) to map the environment. The simulation results show the effectiveness and robustness of the proposed method for mapping.

Design of Suboptimal Robust Kalman Filter for Linear Systems with Parameter Uncertainty (파라미터 불확실성을 갖는 선형 시스템에 대한 준최적 강인 칼만필터 설계)

  • Jin, Seung-Hee;Kim, Kyung-Keun;Park, Jin-Bae;Yoon, Tae-Sung
    • Proceedings of the KIEE Conference
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    • 1997.07b
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    • pp.620-623
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    • 1997
  • This paper is concerned with the design of a suboptimal Kalman filter with robust state estimation performance for system models represented in the state space, which are subjected to parameter uncertainties in both the state and measurement matrices. Under the assumption that the uncertain system is quadratically stable, if the augmented system composed of the uncertain system and the filter is controllable, the proposed filter can provide the upper bound of the estimation error variance for all admissible uncertain parameters. This upper bound can be represented as the convex function of a parameter introduced in the design procedure, and the optimized upper bound of the estimation error variance can also be found via the optimization of this convex function.

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Robust Code Acquisition System in Rayleigh Fading Channel (Rayleigh 페이딩 채널에서 강인한 동기 획득 시스템)

  • 장경운;김기채;박용완
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.11 no.5
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    • pp.723-730
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    • 2000
  • In this paper, we perform a performance analysis of serial acquisition scheme using AWGN rejection filter in Rayleigh fading channel and propose robust acquisition scheme using Reference filter, which is utilized to vary threshold at fading rate, in Rayleigh fading channel. AWGN rejection filter is utilized to evaluate running average for compensating channel gain. The JAKE model, which a channel model, is used for the analysis. The simulation result shows that the mean acquisition time of the proposed acquisition system is minimized than acquisition system using AWGN rejection filter and serial-search acquisition system.

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