• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.6
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• pp.1089-1093
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• 2001

A H$\infty$ control theory is applied to the design problem of synthesis filters in a mutirate filter bank. We select a desired pure time-delay system as reference model, and then consider the error system between the mutirate filter bank and the reference model. 1'he synthesis filters minimize the ι$_2$-induced norm of the error system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.275-278
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• 2001

A H$_{\infty}$ control theory is applied to the design problem of synthesis filters in a mutirate filter bank. We select a desired pure time-delay system as reference model, and then consider the error system between the mutilate filter bank and the reference model. The synthesis filters minimize the ι$_2$-induced norm of the error system.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.2
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• pp.10-18
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• 2003

This paper presents a method for designing guaranteed cost fuzzy filter with a desired H$_{\infty}$ disturbance rejection constraint of delayed fuzzy dynamic systems. This method not only guarantees an induced L$_2$ norm bound constraint on disturbance attenuation, but also minimizes an upper bound on a linear quadratic performance measure. A sufficient condition for the existence of guaranteed cost fuzzy filter with H$_{\infty}$ constraint is then presented in terms of linear matrix inequalities(LMIs). A simulation example is given to illustrate the design procedures and performances of the proposed methods.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.401-404
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• 2003

In this paper, $H_2$, $H_{\infty}$, and mixed $H_2/H_{\infty}$ FIR filters are newly proposed for discrete-time state space signal models. The proposed filters require linearity, unbiased property, FIR structure, and independence of the initial state information in addition to the performance criteria in both $H_2$ and $H_{\infty}$ sense. It is shown that $H_2$, $H_{\infty}$, and mixed $H_2/H_{\infty}$ FIR filter design problems can be converted into convex programming problems via linear matrix inequalities (LMIs) with a linear equality constraint. Simulation studies illustrat that the proposed FIR filter is more robust against uncertainties and has faster convergence than the conventional IIR filters. the conventional IIR filters.

• The Journal of the Acoustical Society of Korea
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• v.23 no.7
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• pp.540-547
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• 2004

Since speech enhancement algorithms based on Kalman/Wiener filter require a priori knowledge of the noise and have focused on the minimization of the variance of the estimation error between clean and estimated speech signal, small estimation error on the noise statistics may lead to large estimation error. However, H/sub ∞/ filter does not require any assumptions and a priori knowledge of the noise statistics, but searches the best estimated signal among the entire estimated signal by applying least upper bound, consequently it is more robust to the variation of noise statistics than Kalman/Wiener filter. In this paper, we Propose a speech enhancement method using HMM and multi H/sub ∞/ filters. First, HMM parameters are estimated with the training data. Secondly, speech is filtered with multiple number of H/sub ∞/ filters. Finally, the estimation of clean speech is obtained from the sum of the weighted filtered outputs. Experimental results shows about 1dB∼2dB SNR improvement with a slight increment of computation compared with the Kalman filter method.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.557-562
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• 2004

This paper deals with a robust mixed ${H_2}/{H_{\infty}}$ filter design problem for a nonlinear dynamic system modeled as a T-S fuzzy system. Integral quadratic constraints are used to describe various kinds of uncertainties of the plant. A sufficient condition for solvability is given in terms of linear matrix inequality problem which can be efficiently solved using a convex optimization technique. In order to demonstrate the Proposed method, a numerical design example is provided.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2002-2004
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• 2003

본 논문에서는 시스템의 모델 불확실성과 백색 가우시안이 아닌 $L_2$ 잡음이 존재하는 경우에 시스템 상태변수의 효과적인 추정을 위한 강인 필터를 제안한다. 제안된 필터는 적분이차제약조건(integral quadratic constraint)을 갖는 일반적인 비선형 불확실 시스템을 위해 선형근사화를 통하여 구성된다. 또한 제안된 필터의 중요한 특성인 변형된 $H{\infty}$ 성능 지수를 유도하고, 해석적 방법을 통해 제안된 필터의 잡음과 시스템 파라미터 불확실성에 대한 강인성을 분석하며, 시뮬레이션 결과를 통하여 제안된 필터가 추정치의 정확도를 효과적으로 향상시키는 것을 보인다.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2002.11a
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• pp.339-342
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• 2002

In the industrial motor drive system which is composed of a motor and load connected with a flexible shaft, a torsional vibration is often generated because of the elastic elements in torque transmission. To solve this problem H$_{\infty}$ controller was designed. In this paper, H$_{\infty}$ control of 2-mass system using H$_{\infty}$ filter for compensating shaft torque is proposed. Pole-zero maps show the validity of proposed controller.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.735-746
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• 1999

We design the robust and inherently fault tolerant decetralized$$H^infty$$ filter for the multisensor state estimation problem when there are insufficient priori informations on the statistical properties of external disturbances. For developing the proposed algorithm, an alternative form of suboptimal$$H^infty$$ filter equations are formulated by applying an alternative form of Kalman filter equations to the indefinite inner product space state model of suboptimal$$H^infty$$ filtering problems. The decentralized$$H^infty$$ filter that consists of local and central fusion filters can be designed effciently using the proposed alternative$$H^infty$$ filiter gain equations. The proposed decentralized$$H^infty$$ filter is robust against un-known external disturbances since it bounds the maximum energy gain from the external disturbances to the estimation errors under the prescribed level$$r^2$$ in both local and central fusion filters and is also fault tolerant due to its inherent redundancy. In addition, the central fusion equations between the global and local data can reduce the unnecessary calculation burden effectively. Computer simulations are made to ceritfy the robustness and fault tolerance of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1464-1468
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• 1997

We propose a decentralized state estimation method in the multisensor state estimation problem. The proposed method bounds teh maximum energy gain from uknown external disturbances to the estimation errors in the suboptimal case. And we formulate aternative H/sip .inf./ filter gain equatiions with teh idea that the suboptimal H.$^{\infty}$ filter is the special form of Kalman filter filter whose state equations are defined in indefinite inner product spaces. Using alternative filter gain equations we design the decentralized $H^{\infty}$ state estimator which is composed of local filters and central fusion filter that are suboptimal in the $H^{\infty}$ sense. In addition, the proposed update equations between global and local data can reduce unnecessary calculation burden efficently.y.