• Proceedings of the IEEK Conference
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• summer
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• pp.97-102
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• 2004

The very complicated proplem in spatial processing is effects of phading (Multipath and Delay Spread) and co-channel interference (CCI). The phading is one of principal causes, that form inter-symbol interference (ISI). Spatial-Temproral Adaptive Filter (STAF) has been taken as a solution of this problem, because it can suppress both these types of interference. But the performance of STAF exposes some elemental limitations, in which are the slow convergence of adaptive process and computational complexity. The cause of this is that, STAF must treat a large quantity of information in both space and time. The way that master these limitation is a use of Subband Spatial-Temproral Adaptive Filter (SSTAF). SSTAF reduce computational complexity by pruning off samples of signal and thus it lost some information in time. This draw on attennation of output SINR of SSTAF. The article analyse a optimal solution of this problem by introducing SSTAF with nonuniform weighted distribution.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.6
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• pp.446-452
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• 2004

Under the condition of a common narrowband target signal and interference signals from several directions, the linearly constrained minimum variance (LCMV) method using the generalized sidelobe canceller (GSC) for adaptive beamforming has been exploited successfully However, in the case of wideband signals, the length of the adaptive filter must be extended. As a result, the complexity of the beamformer increases, which makes real-time implementation difficult. In this paper, we improve the convergence characteristics of the adaptive filter using the transform domain normalized least mean square (NLMS) approach based on the subband GSC structure without the increase of complexity. Besides, the M-MAX algorithm, which is one of various selective coefficient updating methods, is employed in order to remarkably reduce the computational cost without decreasing the convergence quality. With the combination of these methods, we propose a computationally efficient wideband adaptive beamformer and verify its efficiency through a series of simulations.

• The Journal of the Acoustical Society of Korea
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• v.17 no.2E
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• pp.3-9
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• 1998

Since the introduction of hands-free phone set and teleconferencing system, acoustic echo cancellation has been a challenge for engineers. Recently many researches have shown that the best solution for the acoustic echo compensation problem is represented by an adaptive filter which iteratively tries to identify the unknown impulse response of the system from loudspeaker to microphone. In this paper, we apply the delayless subband adaptive filters and fast affine projection algorithm for the identification of room impulse response. Simulation results show 3∼8 dB more enhanced performance than conventional fullband adaptive filters or subband adaptive filters. In addition, fast affine projection algorithm shows better convergence speed at the expense of the low computational complexity than conventional LMS algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.1
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• pp.162-167
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• 2012

In power quality monitoring, it is very important to detect disturbances (sag, swell, transient, and interruption) accurately. In this paper, a detection method for power quality disturbances by combining the filter bank system and adaptive filter is proposed. To decompose power signal, binary tree structured filter bank system is designed. In the filter bank system, the fundamental filter bank(QMF bank) is used as a module in each decomposing level. An adaptive filter is used to improve the detection accuracy of disturbances for each subband signal. In the adaptive filter, the measure of estimated error change is used to detect singular points of power quality disturbances. Computer simulations were performed on synthetic signals which have disturbances to assess the performance of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.407-416
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• 2000

Adaptive digital filtering and noise cancelling technique using a tree structured filter bank are presented to reduce a undesirable aliasing due to the decimation of filtered output and improve the performance in terms of mean-square error and the convergence speed using a aliasing canceller. A signal is split into two subband by analysis filter bank and decimated by decimator and reconstructed by interpolation technique and synthesis filter bank. A variable step-size LMS algorithm is used to improve the convergence speed in case of existing the measurement noise in desired input of filter. It is shown by computer simulation that the proposed subband structure in this paper is superior to conventional subband filter structure in terms of mean-square error and convergence speed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.443-448
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• 2022

This paper presents a subband affine projection algorithm with variable step size to improve convergence performance in adaptive filtering applications with long adaptive filters and highly correlated input signals. The proposed algorithm can obtain fast convergence speed and small steady-state error by using different step sizes for each adaptive sub-filter in the subband structure to which polyphase decomposition and noble identity are applied. The step size derived to minimize the mean square error of the adaptive filter at each update time shows better convergence performance than the existing algorithm using a variable step size. In order to confirm the convergence performance of the proposed algorithm, which is superior to the existing algorithm, computer simulations are performed for mean square deviation(MSD) for AR(1) and AR(2) colored input signals considering the system identification model.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.77-84
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• 2017

Generally, a time-varying vibration signal is generated in a rotating machine system, and when there is a failure in the rotating machine, the signal contains noise. In this paper, we propose a system consisting of an adaptive predictor and a binary tree filter bank for analyzing time - varying vibration signals with noise. And the vibration signal analyzed results in this system is used for fault diagnosis of the rotating machine. The adaptive predictor of the proposed system predicts the periodic signal components, and the filter bank system decomposes the difference signal between the input signal and the predicted periodic signal into subband. Since each subband signal includes a noise signal component due to a failure, it is possible to diagnose the failure of the using rotary machine. The validity of the proposed vibration signal analysis method is shown in the simulations, where the periodic components cancelled vibrating signals are decomposed to 32 subband, and the signal characteristics related faults are analyzed.

• Journal of Internet Computing and Services
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• v.2 no.3
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• pp.27-36
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• 2001

Recently much attention has been paid for interference mitigation technique for the COMA system, since more capacity is available with same bandwidth. In this paper, we introduces a novel adaptive interference suppression techniques for the CDMA system with narrow band interference. The proposed interference rejection scheme employs the adaptive linear prediction techniques in the subband. In each subband, we can more easily find and cancel the narrow band signal as compared to the full band. Thus, the proposed interference rejection can be classified as another time-frequency techniques for the narrow band interference rejection(10). Computer simulation is conducted for the 3-G COMA system with IF band sampling techniques, yielding better interference rejection and bit error rate performance as compared to conventional one. Also, optimum filter is analyzed and from the analysis, it can be shown the subband prediction techniques can suppress narrow band interference more efficiently.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.3
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• pp.501-507
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• 1999

At the mobile unit for adaptation the propagation environment, it is necessity to adapt very fast the weight coefficient vector of adaptive array antenna In this paper, for the BPSK and BFSK signals with S/I=2, S/N=10 subband adaptive array signal processing method to the linear array antenna using the LMS & the Kalman filter algorithm is proposed. For the 4 elements equidistance linear array antenna systems LMS and Kalman algorithms with subband adaptive instruction principles using the subband signal processing method are adopted and the computer simulation results to the constant amplitude envelope signals such as BPSK or BFSK can be seen that the convergence characteristics of directional patterns and the signal following characteristics are more fast and stable.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.12
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• pp.2772-2782
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• 1997

In this paepr, a Wiener filtering method in wavelet domain is proposed for restoring an image corrupted by additive white noise. The proposed method utilizes the characteristics of wavelet transform signals and the local statistics of each subband. When estimating the local statistics in each subband, the size of filter window is varied according to each scale. At this point, the local statistics in each wavelet subband is estimated only by using pixedls which have similar statistical property. Experimental results show that the proposed method has better performance over the conventional Lee filter with a window of fixed size.