• The Journal of the Acoustical Society of Korea
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• v.26 no.2
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• pp.69-74
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• 2007

In signal processing applications with highly correlated input signals, subband affine projection algorithm and step size controlling is a good solution for improving the slow convergence rate and large computational complexity of LMS-type algorithms. This paper proposes a subband affine projection algorithm using a variable step size. The proposed method achieves fast convergence rate and small steady-state error with a small computational complexity by combining the SAP and step size controlling in a subband structure. Experimental results on highly correlated input signal show that the proposed method is superior to the conventional methods.

• 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 Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.474-476
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• 2009

In the radio communication, such as echo cancellation and channel equalization, adaptive filtering is very practical. Its convergence behavior that is used for updating the weights depends on the correlation of the input signal and length of adaptive filter. Highly correlated input and long length of adaptive filter deteriorate the convergence behavior. To solve this problem, recently, subband affine projection algorithm which pre-whiten the correlation of the input and update the weights in subband structure has been presented. This paper presents convergence analysis method of multiple constrained subband affine projection algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.238-243
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• 2010

A new implementation method for MPDSAP(Maximally Polyphase Decomposed Subband Affine Projection) adaptive filter is proposed. The affine projection(AP) adaptive filter achieves fast convergence speed, however, its implementation is so expensive because of the matrix inversion for a weight-updating of adaptive filter. The maximally polyphase decomposed subband filtering allows the AP adaptive filter to avoid the matrix inversion, moreover, by using a pipelining technique, the simple subband structured AP is suitable for VLSI implementations concerning throughput, power dissipation and area. Computer simulations are presented to verify the performance of the proposed algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.476-483
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• 2010

If the data are pre-whitened, then gradient adaptive algorithms which are simpler than higher order statistics algorithms can be used in adaptive blind signal estimation. In this paper, we propose a blind subband affine projection algorithm for multiple-input multiple-output adaptive equalization in the blind environments. All of the adaptive filters in subband affine projection equalization are decomposed to polyphase components, and the coefficients of the decomposed adaptive sub-filters are updated by defining the multiple cost functions. An infinite impulse response filter bank is designed for the data pre-whitening. Pre-whitening procedure through subband filtering can speed up the convergence rate of the algorithm without additional computation. Simulation results are presented showing the proposed algorithm's convergence rate, blind equalization and blind signal separation performances.

• 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.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.883-887
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• 2009

This paper presents a statistical analysis of the MSE of adaptation for the MPDSAP (Maximally polyphase decomposed Subband Affine Projection) algorithm for the an autoregressive (AR) inputs with P order. In subband structure, the Affine Projection (AP) algorithm is transformed to the Normalized Least Mean Square (NLMS) algorithm by applying the polyphase decomposition and the noble identity to the adaptive filter. And also, AR input can be pre-whitened by subband filtering with the Orthonormal Analysis Filters(OAF). In the subband structure, the pre-whitening of the AR(P) inputs provides simple and valid approximations for a statistical analysis of the MSE behaviors for the SAP adaptive filter.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.145-156
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• 2005

In application for acoustic echo cancellation and adaptive equalization, input signal is highly correlated and the long length of adaptive filter is needed. Affine projection algorithms, in these applications, can produce a good convergence performance. However, they have a drawback that is a complex hardware implementation. In this paper, we propose a new subband affine projection algorithm with improved convergence and reduced computational complexity. In addition, we suggest a good approach to implement the proposed method. In this method by applying polyphase decomposition, noble identity and critical decimation to the anne projection algorithm the number of input vectors for decorrelation can be reduced. The weight-updating formula of the proposed method is derived as a simple form that compared with the NLMS(normalized least mean square) algorithm by the reduced projection order The efficiency of the proposed algorithm for a colored input signal was evaluated by using computer simulations.

• 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.