• 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.

• 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.

• 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 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.