• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.182-185
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• 2000

In this paper, we present a new adaptive filter structure which is based on polyphase decomposition of the filter to be adapted. This structure uses wavelet transform to acquire transform-domain coefficients of the input signal. With this coefficients RLS algorithm is used for adaptation. Particularly, using the polyphase parallel structure, we can trace the system which has very long impulse response with only increasing the subband, and show that computational savings can be achieved. The proposed structure was applied to system identification for performance estimation and compared with fullband adaptive filter.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.20-25
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• 2011

In subband structure, the fullband AP adaptive filter with P projection dimension can be decomposed P adaptive sub-filters by applying maximally polyphase decomposition and noble identity. Each adaptive sub-filter has a simple weight update formula with the unit projection dimension. This subband decomposition method is one of the most practical solution in the viewpoint of implementation. For utilization in many applications, it is necessary that analysis for the optimum step size of the maximally polyphase decomposed subband AP(MPDSAP) adaptive filter. In this paper, we present an improved analysis model of mean square error and induce the initial optimum step size for the MPDSAP adaptive filter. Computer simulations show that there is a relatively good match between theory and practice for the improved analysis model of MSE and the induced initial optimum step size.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.423-430
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• 2011

In adaptive filtering, the sparseness of impulse response and input signal characteristics are very important factors of it's performance. This paper presents a subband improved proportionate normalized least square (SIPNLMS) algorithm which combines IPNLMS for impulse response sparseness and subband filtering for prewhitening the input signal. As drawing and combining the advantage of conventional approaches, the proposed algorithm, for impulse responses exhibiting high sparseness, achieve improved convergence speed and tracking ability. Simulation results, using colored signal(AR(4)) and speech input signals, show improved performance compared to fullband structure of existing methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.104-110
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• 2009

In this paper, we suggest a new technique which employ the pipelined architecture for the implementation of the SAP adaptive filter using variable step size. According as SAP adaptive filter is sufficiently decomposed, a simplified SAP adaptive filter can be derived, and the weights of adaptive sub-filters can be updated by a simple formular without a matrix inversion. The convergence speed and the steady state error of the simplified SAP adaptive filter are improved by using variable step size. For practical implementation, the simplified SAP adaptive sub-filters are transformed by the pipeline technique.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.163-174
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• 2009

Applying the maximally polyphase decomposition and noble identity to the adaptive filter in subband structure, the conventional fullband affine projection algorithm is translated to the subband affine projection (SAP) algorithm. The Maximally polyphase decomposed SAP (MPDSAP) algorithm is a special version of the SAP algorithm, and its adaptive sub-filters have unity projection dimension. The weight updating formular of the MPDSAP is similar to that of the NLMS algorithm, so it may be more proper algorithm than other AP-type algorithms for many practical applications. This paper presents a new statistical analysis of the MPDSAP algorithm. The analytical model is derived for autoregressive (AR) inputs and the nonunity adaptive gain in the subband structure with the orthonormal analysis filters (OAF), The pre-whitening by the OAF allows the derivation of a simple-analytical model for the MPDSAP with the AR inputs and the nonunity adaptive gain.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.4
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• pp.679-687
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• 2009

In this paper, a subband filtering and adaptive prediction technique for analyzing harmonics in power systems is presented. In this method, the filter banks are designed to decompose odd and even order harmonics separately. The adaptive prediction has been employed reduce the transient and white noise effect in time varying harmonics detecting and tracking. The frequencies and amplitudes of the decomposed harmonics are estimated by recursive algorithm. To demonstrate the performances of the developed technique, computer simulations to the signal with the time-varying frequency and THD are carried out.

• The Journal of the Acoustical Society of Korea
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• v.32 no.6
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• pp.518-524
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• 2013

In this paper, we propose a variable step size algorithm to enhance the normalized subband adaptive filter which has been proposed to improve the convergence characteristics of the conventional full band adaptive filter. The well-known Kwong's variable step size algorithm is simple, but shows better performance than that of the fixed step size algorithm. However, in case that large additive noise is present, the performance of Kwong's algorithm is getting deteriorated in proportion to the amount of the additive noise. We devised a variable step size algorithm which does not depend on the amount of additive noise by exploiting a normalized adaptation error which is the error subtracted and normalized by the estimated additive noise. We carried out a performance comparison of the proposed algorithm with other algorithms using a system identification model. It is shown that the proposed algorithm presents good convergence characteristics under both stationary and non-stationary environments.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.677-680
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• 1998

In this paper, we proposed a lwo bit rate subband coding with adaptive vector quantization using the correlation between motion vector and block energy in subband. In this method, the difference between the input signal and the motion compensated interframe prediction signal is decomposed into several narrow bands using quadrature mirror filter (QMF) structure. The subband signals are then quantized by adaptive vector quantizers. In the codebook generating process, each classified region closer to the block value in the same region after the classification of region by the magnitude of motion vector and the variance values of subband block. Because codebook is genrated considering energy distribution of each region classified by motion vector and variance of subband block, this technique gives a very good visual quality at low bit rate coding.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.1
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• pp.94-101
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• 2000

In this paper, a multi-channel active noise control(ANC) system using subband hybrid control techniques is proposed. Subband techniques could reduce computational burden and improve the performance of ANC systems by dividing several frequency subband and adjusting adaptive filter coefficients. So it can effectively cancel noises at wanted frequency range and use lower order adaptive filter than the existing algorithms. The adjoint LMS algorithm, which prefilter the error signals instead of the divided reference signals in frequency band, is also used for adaptive filter algorithms to reduce the computational burden of the subband adaptive systems. To improve performance of the ANC system, a weighted hybrid control technique, which has weightily properties of feedforward control systems and feedback control systems, is applied. This algorithm shows higher stability and good noise attenuation property in broad band ANC systems. Computer simulations were performed to show the effectiveness of the proposed algorithm.

• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.347-355
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• 2000

This paper presents an adaptive AEC(acoustic echo canceller) based on the wavelet transform using M-channel subband QMF filter banks. The proposed algorithm improves the performance of AEC with a realtime process by a low complexity of wavelet transform filter banks, a subband processing and a orthogonality of wavelet subband filter. Adaptive filter coefficients of each subband are updated using LMS algorithm with a low complexity and a easy realization for a realtime processing and a reduction of hardware cost. For a input signal, a white Gaussian noise and a real speech signal with a environment noises are used for a performance estimation of the proposed algorithm. As a result of computer simulation, the proposed AEC has a low asymptotic error, a low computation complexity and a robust performance.