• The Journal of the Acoustical Society of Korea
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• v.29 no.1
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• pp.18-23
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• 2010

The RLS (Recursive Least Squares) method is a broadly used adaptive algorithm for signal processing in electronic engineering. The RLS algorithm shows a good performance and a fast adaptation within a stationary environment, but it shows a Poor performance within a non-stationary environment because the method has a fixed forgetting factor. In order to enhance 'tracking' performances, BLS methods with an adaptive forgetting factor had been developed. This method shows a good tracking performance, however, it suffers from heavy computational loads. Therefore, we propose a modified AFF-RLS which has relatively low complexity m this paper.

• Smart Structures and Systems
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• v.32 no.1
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• pp.9-21
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• 2023

The parameters of civil engineering structures have time-variant characteristics during their service. When extremely large external excitations, such as earthquake excitation to buildings or overweight vehicles to bridges, apply to structures, sudden or gradual damage may be caused. It is crucially necessary to detect the occurrence time and severity of the damage. The unscented Kalman filter (UKF), as one efficient estimator, is usually used to conduct the recursive identification of parameters. However, the conventional UKF algorithm has a weak tracking ability for time-variant structural parameters. To improve the identification ability of time-variant parameters, an adaptive UKF with forgetting factor (AUKF-FF) algorithm, in which the state covariance, innovation covariance and cross covariance are updated simultaneously with the help of the forgetting factor, is proposed. To verify the effectiveness of the method, this paper conducted two case studies as follows: the identification of time-variant parameters of a simply supported bridge when the vehicle passing, and the model updating of a six-story concrete frame structure with field test during the Yangbi earthquake excitation in Yunnan Province, China. The comparison results of the numerical studies show that the proposed method is superior to the conventional UKF algorithm for the time-variant parameter identification in convergence speed, accuracy and adaptability to the sampling frequency. The field test studies demonstrate that the proposed method can provide suggestions for solving practical problems.

• The Transactions of the Korea Information Processing Society
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• v.5 no.10
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• pp.2725-2736
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• 1998

In this paper. we present a new pitch determination method for speech analysis. namely VFF(Variable Forgetting Factor) based. by using the WRLS-VFF-VT(Weighted Recursive Least Square-Variable Forgetting Factor-Variable Threshold) algorithm. A proposed method uses VFF to identify the glottal closure points which correspond to the instants of the main excitation pulses for voiced speech. The modified EGG

• The Journal of the Acoustical Society of Korea
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• v.25 no.4E
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• pp.154-158
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• 2006

In this paper, we suggest a noise estimation method for speech enhancement in nonstationary noisy environments. The proposed method consists of the following two main processes. First, in order to receive fewer affect of variable signals, a best fitting regression line is used, which is obtained by applying a least squares method to coefficient magnitudes in a node with a uniform wavelet packet transform. Next, in order to update the noise estimation efficiently, a differential forgetting factor and a correlation coefficient per subband are used, where subband is employed for applying the weighted value according to the change of signals. In particular, this method has the ability to update the noise estimation by using the estimated noise at the previous frame only, without utilizing the statistical information of long past frames and explicit nonspeech frames by voice activity detector. In objective assessments, it was observed that the performance of the proposed method was better than that of the compared (minima controlled recursive averaging, weighted average) methods. Furthermore, the method showed a reliable result even at low SNR.

• The Korean Journal of Food And Nutrition
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• v.1 no.2
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• pp.31-36
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• 1988

An adaptive on-line optimization method has been applied to test the ability to maximize the cellular productivity of a continuous methylotroph culture system which was simulated by a variable yield Monod-type model. Optimum dilution rate and productivity were successively obtained and maintained at all times by the algorithm that utilizes steepest descent technique as optimization method and recursive least-square method with forgetting factor as dynamic model identification.

• The Journal of the Acoustical Society of Korea
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• v.12 no.1E
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• pp.56-64
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• 1993

본 논문은 공간적으로 변하는 스펙트럼을 추정하는 새로운 적응 방법을 제안한다. 제안한 방법에서는 오래된 upstream의 데이터를 망각함으로서 신호의 nonstationarity를 고려해주는 시변망각인자의 개념을 recursive least square(RLS) 알고리즘에 도입하였으며, 관심이 있는 공간영역에서 탐사침을 천천히 움직여 얻은 하나의 데이터 군으로부터 downstream 스펙트럼을 추정하였다. 제시한 방법의 실현 가능성은 실제 실험(wind tunnel 이용)을 통해서 얻은 공간적으로 변하는 nonstatonary 신호의 스펙트럼을 추정하는 과정에서 입증되며 또한 기존의 방법들과 비교함으로서 그 우수성을 보인다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1280-1287
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• 2006

We propose a modified stochastic gradient-based (MSGB) filter showing that the filter is the solution to an optimization problem. This paper analyzes the properties of the MSGB filter that corresponds to the nonlinear adaptive filter with additional update terms, parameterized by the variable scaling factor. The variably parameterized MSGB filter plays a role iii connecting the fixed parameterized MSGB filter and the null parameterized MSGB filter through variably scaling parameter. The stability regions and misadjustments are shown. A system identification is utilized to perform the computer simulation and demonstrate the improved performance feature of the MSGB filter.

• Proceedings of the KIEE Conference
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• 2001.05a
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• pp.210-213
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• 2001

This study presents an effective variable forgetting factor method based on fuzzy logic to suppress frequency droop in extended integral load frequency control. The performance of the extended integral control is greatly dependent on the decaying factor. For an optimal or near optimal performance, it is necessary that the decaying factor as well as the feedback gains should be changed very quickly in response to changes in the system dynamics. However, because of its time-varing characteristic, the optimal decaying factor is difficult to be selected analytically. By adopting fuzzy set theory, the decaying factor can be determined quickly to respond to the variation of the feedback signals. This study builds a fuzzy rule base with use of the change of frequency and its rate as inputs. The computer simulation has been conducted for the single machine system. The simulation results show that the proposed fuzzy 1o81c based controller yields more improved control performance than the conventional PI controller.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.355-358
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• 2000

기존의 Rayleigh fading 환경에서 칼만 필터를 사용한 다중 사용자 검출에서는 비동기적으로 들어온 다른 사용자 신호의 상태가 바뀜에 따라서 수렴하던 신호에 영향을 미친다. 이러한 특성은 결국 전체 시스템에 영향을 미쳐서 검출 성능을 떨어뜨린다. 본 논문에서는 에러가 발생하였을 때의 경우를 고려하기 위해 VFF(Variable forgetting factor)를 도입하였고 이를 이용해 추정된 신호의 가중 합을 기반으로 시스템을 구성한 결과 성능이 향상되었음을 보이고자 한다.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06e
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• pp.165-168
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• 1998

본 논문에서는 충격성 잡음에 강인하기 위한 시변 주파수 추정 기법을 제안하였다 충격성 잡음에 강인하기 위해서는 충격성 잡음에 의한 추정 변수의 동요를 제한하고 추정된 오차가 향후 추정시 영향을 미치는 오차의 전파현상을 제한하여야 한다. 충격성 잡음에 의한 추정오차의 전파를 제한하기 위해서는 망각인자의 도입이 필요함을 증명하였고 보다 효과적으로 사용하기 위해서 가변 망각인자를 도입하였다. 가변 망각인자의 도입으로 충격성 잡음에 의한 오차의 전파를 선택적으로 제한할 수 있으며 충격성 잡음에 의한 추정계수의 변동은 영향함수 측면에서 Huber함수를 이용하여 제한하였다. 제안된 알고리듬은 Huber함수와 가변망각인자의 도입으로 충격성 잡음에 의해 생기는 오차의 크기와 오차의 영향이 전파되는 것을 적응적으로 제한하기 때문에 모의실험을 통해 기존의 칼만 알고리듬보다 나은 성능을 보임을 알 수 있었다.