• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.521-521
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• 2000

This paper investigates the problem of robust H$_{\infty}$ filter with FIR(Finite Impulse Response) structure for linear continuous time-varying systems with sampled-data measurements. It is assumed that the system is subject to real time-varying uncertainty which is represented by the state-space model having parameter uncertainty. The robust H$_{\infty}$ FIR filter is proposed for the continuous-time linear parameter uncertain systems. It is also derived from the equivalence relationship between the robust linear H$_{\infty}$ FIR filter and the robust linear H$_{\infty}$ filter with sampled-data measurements.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.3
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• pp.163-168
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• 2000

The problems of mixed $H_2/H_{\infty}$ filtering design fer continuous and discrete time linear systems with time delay are investigated. The main purpose is to design a stable mixed $H_2/H_{\infty}$ filter which minimizes the H$_2$Performance measure satisfying a prescribed H$_{\infty}$ norm bound on the closed loop system in continuous-time case and discrete-time case, respectively. The sufficient conditions of existence of filter, the mixed $H_2/H_{\infty}$ filter design method, and the upper bound of performance measure are proposed by LMI(linear matrix inequality) techniques in terms of all finding variables. Also, we present optimization problems in order to get the optimal mixed $H_2/H_{\infty}$ filter in continuous and discrete time case, respectively.

• International Journal of Control, Automation, and Systems
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• v.5 no.4
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• pp.355-363
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• 2007

The paper deals with the Kalman stochastic filtering problem for linear continuous-time systems with both instantaneous and time-delayed measurements. Different from the standard linear system, the system state is corrupted by multiplicative white noise, and the instantaneous measurement and the delayed measurement are also corrupted by multiplicative white noise. A new approach to the problem is presented by using projection formulation and reorganized innovation analysis. More importantly, the proposed approach in the paper can be applied to solve many complicated problems such as stochastic $H_{\infty}$ estimation, $H_{\infty}$ control stochastic system with preview and so on.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.5
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• pp.22-28
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• 2009

In this paper, we consider the problem of $H_{\infty}$ filtering for continuous-time singular systems with multiple state-delays. The aim of designed filter is to guarantee regularity, impulse-free, asymptotic stability and $H_{\infty}$ norm bound of filtering error singular system. By establishing a finite sum inequality based on quadratic terms, a new delay-dependent BRL (bounded real lemma) for singular systems with multiple state-delays is derived. Based on the result, the existence condition of $H_{\infty}$ filter and filter design method are proposed in terms of LMI (linear matrix inequality). Finally, a numerical example is provided to show the validity of the design methods.

• Journal of KIEE
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• v.11 no.1
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• pp.21-26
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• 2001

This paper considers the problem of robust H$\infty$ filter is derived by using the equivalence relationship between the FIR filter and the recursive filter, that would be guarantee a prescribed H$\infty$ performance in the continuous-time context, irrespective of the parameter uncertainty and unknown initial states.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.83-88
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• 2001

The robust linear H(sub)$\infty$ FIR filter, which guarantees a prescribed H(sub)$\infty$ performance, is designed for continuous time-varying systems with unknown cone-bounded nonlinearity. The infinite horizon filtering for time-varying systems is systems is investigated in therms of two Riccati equations by the finite moving horizon.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.615-619
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• 2009

A real-time, continuous-scale image interpolation method is proposed based on bi-linear interpolation with directionally adaptive low-pass filtering. The proposed algorithm has been optimized for hardware implementation. The original bi-linear interpolation method has blocking artifact. The proposed algorithm solves this problem using directionally adaptive low-pass filtering. It can also solve the severely problem by selection choosing low-pass filter coefficients. Therefore the proposed interpolation algorithm can realize a high-quality image scaler for various imaging systems, such as digital camera, CCTV and digital flat panel display, to name a few.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.16-21
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• 2005

This paper considers the problem of state estimation in linear continuous-time systems with multi-sensor environment and observation uncertainties. We propose two suboptimal filtering algorithms for these types of systems. The filtering algorithms consist of two steps: The local optimal Kalman estimates are computed at the first step. And, these local estimates are lineally fused at the second step. The implementation of the two-step filtering algorithms needs a lower memory demand than the optimal Kalman and adaptive Lainiotis-Kalman filters. In consequence of parallel structure of the proposed filters, the parallel computers can be used for their design. The examples exhibit the effect of common noise on the performance of fusion of the local Kalman estimates based on observations from different sensors and in the presence of uncertainties.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.3
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• pp.128-134
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• 2014

A real-time, continuous-scale image interpolation method is proposed based on a bilinear interpolation with directionally adaptive low-pass filtering. The proposed algorithm was optimized for hardware implementation. The ordinary bi-linear interpolation method has blocking artifacts. The proposed algorithm solves this problem using directionally adaptive low-pass filtering. The algorithm can also solve the severe blurring problem by selectively choosing low-pass filter coefficients. Therefore, the proposed interpolation algorithm can realize a high-quality image scaler for a range of imaging systems, such as digital cameras, CCTV and digital flat panel displays.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.1045-1050
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• 1988

The problem of applying the linear integral filter in analysis and parameter estimation of linear continuous systems is discussed. A discrete-time model, which is equivalent to that obtained using the bilinear z transformation, is derived and employed to predict system output. It is shown that the output error can be controlled through the sampling interval. In order to obtain unbiased estimates, an instrumental variable (IV) method is proposed, where the instrumental variables are constituted using adaptive filtering. Some problems on implementation of the recursive IV algorithm are discussed. Both theoretical analysis and simulation study are given to illustrate the proposed methods.