• The Journal of the Acoustical Society of Korea
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• v.23 no.3
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• pp.221-227
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• 2004

This paper presents the subband affine projection algorithm(SAPA). The improved performance of SAPA is achieved by applying the affine projection algorithm to the subband adaptive structure. In this algorithm, the weight updating formula of adaptive filter is simply derived by using the orthogonal quadrature filter(OQF) as an analysis filter bank for subband filtering. The derived SAPA has the fast convergence speed and small computational complexity. The efficiency of the proposed algorithm for colored input signal is evaluated through some experiments.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.210-212
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• 2009

In object tracking based on the particle filter algorithm controlling the proper distribution of the samples is essential to accurately track the target. If the samples are spread too wide compared to the target size, the tracking accuracy may degrade as some samples can be caught by background clutters that is similar to the target. On the other hands if the samples are spread too narrow, the particle filter may fail to track the abrupt motion of the target. To solve this problem we propose an improved particle filter that adopts "re-weighting" technique at the observe step. We estimate the distribution of the weights of the current samples by its mean and variance. Then the samples are re-weighted so that the appropriate distribution of the samples in proportional to the target scale is obtained at the next select step. The proposed tracking method can avoid convergence to local mean and improve the accuracy of the estimated target state.

• Speech Sciences
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• v.11 no.2
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• pp.227-235
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• 2004

In this paper, we proposed a new practical implementation method of the lattice transversal joint (LTJ) adaptive filter using speech codec's information. And it was applied to the adaptive echo cancellation problem to verify the efficiency of the proposed method. Realtime implementation of the LTJ adaptive filter is very difficult due to high computational complexity for the filter coefficients compensation. However, in case of using speech codec, complexity can be reduced since linear predictive coding (LPC) coefficients are updated each frame or sub-frame instead of every sample. Furthermore, LPC coefficients can be acquired from speech decoder and transformed to the reflection coefficients. Therefore, the computational complexity for updates of the reflection coefficients can be reduced. The effectiveness of the proposed LTJ adaptive filter was verified by the experiments about convergence and tracking performance of the adaptive echo canceller.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.645-652
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• 2006

In this paper a new type of filter, called the $H_2/H_{\infty}$ FIR filter, is proposed for discrete-time state space signal models. The proposed filter requires 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 $H_2/H_{\infty}$ FIR filter design problems can be converted into convex programming problems via linear matrix inequalities (LMIs) with a linear equality constraint. Simulation studies illustrate that the proposed FIR filter is more robust against temporary uncertainties and has faster convergence than the conventional IIR filters.

• East Asian mathematical journal
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• v.28 no.3
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• pp.293-303
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• 2012

Sequential quadratic programming (SQP) has been one of the most important methods for solving nonlinear constrained optimization problems. Recently, filter method, proposed by Fletcher and Leyffer, has been extensively applied for its promising numerical results. In this paper, we present and study an active set SQP-filter algorithm for inequality constrained optimization. The active set technique reduces the size of quadratic programming (QP) subproblem. While by the filter method, there is no penalty parameter estimate. Moreover, Maratos effect can be overcome by filter technique. Global convergence property of the proposed algorithm are established under suitable conditions. Some numerical results are reported in this paper.

• Journal of IKEEE
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• v.17 no.2
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• pp.111-118
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• 2013

In this paper, the subband nonlinear adaptive Volterra filters are introduced and its analysis are presented. From the eigenvalue analysis of the input correlation matrix, we show that the proposed subband adaptive Volterra filter has superior convergence performance as compared to the conventional one, which shows that the it can be useful for the recently proposed subband nonlinear adaptive echo canceller. Also, the optimum filter in each subband are introduced and verified from the computer simulations.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.269-274
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• 2010

After introducing many different types of prefilter convergence, we introduce an universal method to define various notions of compactness using cluster point and convergence of a prefilter and to prove the Tychonoff theorem using characterizations of ultra(maximal) prefilters.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.941-943
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• 1995

The convergence of adaptive algorithm depends mainly on the proper choice of the design factor called the covergence factor. In the paper, an optimal convergence factor involved in TRLMS algorithm, which is used to predict the coefficients of the ARMA predictor in ADPCM is presented. It is shown that such an optimal value can be generated by system signals such that the adaptive filter becomes self optimizing in terms of the convergence factor. This algorithm is applied to real image.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.377-380
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• 2002

When it calculates the optimum price of filter coefficient, the many operation quantity is necessary. Is like that the real-time control is difficult and the hardware embodiment expense is big. The case which does not know advance information of input signal or the case where the statistical nature changes with change of surroundings environment is necessary the adaptive filter. Every hour to change a coefficient automatically and system in order to reach to the condition of optimum oneself, the fact that is the adaptive filter. When it does not the quality of input signal or it does not know the environment of surroundings every hour changing, it does not emit not to be, in order to collect, the fact that is the adaptive filter. The case of the Acoustic Echo Canceler does thousands filter coefficients in necessity. It reduces a many calculation quantity to respect, it uses the IIR filter from hour territory. Also it uses the block adaptive filter which has a block input signal and a block output signal. The former there is a weak point where the stability discrimination is always demanded. Consequently, The block adaptive filter is researched plentifully. This dissertation planned the block MADF adaptive filter used to MADf algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.3
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• pp.612-621
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• 1996

In this paper, we propose the low sidelobe digital FIR doppler filter bank synthesis algorithm through the Gradient Descent method and it can be practially appliable to coherent pulse doppler radar signal processing. This algorithm shows the appropriate calculation of tap coefficients or zeros for FIR transversal fiter which has been employed in radar signal processor. The span of the filters in the filter bank be selected at the desired position the designer want to locate, and the lower sidelobe level that has equal ripple property is achieved than one for which the conventional weithtedwindow is used. Especially, when we implemented filter zeros as design parameters it is possible to make null filter gain at zero frequency intensionally that would be very efficient for the eliminatio of ground clutter. For the example of 10 tap filter synthesis, when filter coefficients or zeros are selected as design parameters the corresponding sidelobelevel is reducedto -70db or -100db respectively and it has good convergent characteristics to the desired sidelobe reference value. The accuracy ofapproach to the reference value and the speed of convergence that show the performance measure of this algorithm are tuned out with some superiority and the fact that the bandwidth of filter appears small with respect to one which is made by conventional weighted window method is convinced. Since the filter which is synthesized by this algorithm can remove the clutter without loss of target signal it strongly contributes performance improvement with which detection capability would be concerned.