In this letter, a multichannel controller based on Volterra filters is described. A filtered-X affine projection algorithm is derived in detail for homogeneous quadratic filters. The proposed algorithm can be also ext...
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In this letter, a multichannel controller based on Volterra filters is described. A filtered-X affine projection algorithm is derived in detail for homogeneous quadratic filters. The proposed algorithm can be also extended to higher-order Volterra kernels and includes linear controllers as a particular case.
This paper presents a numerical expression for the excess mean-square error(EMSE) of affineprojection(AP) algorithms, and the expression is proportional to the data reuse factor and the condition number of the input ...
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This paper presents a numerical expression for the excess mean-square error(EMSE) of affineprojection(AP) algorithms, and the expression is proportional to the data reuse factor and the condition number of the input data. For the condition number, a recently reported technique developed by using E-norm is adopted instead of L{sub}2-norm The proposed expression offers an insight into the mechanics of the AP algorithm by including the condition number in the EMSE. Our simulation results show a relatively good match between the proposed expression and the practice.
This paper provides an analysis of transient and steady-state behavior of different filtered-x affine projection algorithms. algorithms suitable for single-channel and for multichannel active noise controllers are tre...
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This paper provides an analysis of transient and steady-state behavior of different filtered-x affine projection algorithms. algorithms suitable for single-channel and for multichannel active noise controllers are treated within a unified framework. Very mild assumptions are posed on the active noise control system model, which is only required to have a linear dependence of the output from the filter coefficients. Therefore, the analysis applies not only to the linear finite impulse response models but also to nonlinear Volterra filters, i.e., polynomial filters, and other nonlinear filter structures. The convergence analysis presented in this paper relies on energy conservation arguments and does not apply the independence theory, nor does it impose any restriction to the signal distributions. It is shown in the paper that filtered-x affine projection algorithms always provide a biased estimate of the minimum mean square solution. Nevertheless, in many cases, the bias is small and therefore these algorithms can be profitably applied to active noise control.
affine projection algorithms are useful adaptive filters whose main purpose is to speed the convergence of LMS-type filters. Most analytical results on affine projection algorithms assume special regression models or ...
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affine projection algorithms are useful adaptive filters whose main purpose is to speed the convergence of LMS-type filters. Most analytical results on affine projection algorithms assume special regression models or Gaussian regression data. The available analysis also treat different affineprojection filters separately. This paper provides a unified treatment of the mean-square error, tracking, and transient performances of a family of affine projection algorithms. The treatment relies on energy conservation arguments and does not restrict the regressors to specific models or to a Gaussian distribution. Simulation results illustrate the analysis and the derived performance expressions.
This letter proposes two new variable step-size algorithms for normalized least mean square and affineprojection. The proposed schemes lead to faster convergence rate and lower mis-adjustment error.
This letter proposes two new variable step-size algorithms for normalized least mean square and affineprojection. The proposed schemes lead to faster convergence rate and lower mis-adjustment error.
This paper presents a novel blind adaptive array algorithm for CDMA systems employing the despread-respread technique in conjunction with the Block affine projection algorithm. The Block affineprojection Despread Res...
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ISBN:
(纸本)0780385217
This paper presents a novel blind adaptive array algorithm for CDMA systems employing the despread-respread technique in conjunction with the Block affine projection algorithm. The Block affineprojection Despread Respread Multitaraget Array (AP-DRMTA) algorithm is developed and compared with the Least Squares Despread Respread Multitarget Array (LS-DRMTA) algorithm, the Least Squares Despread Respread Multitarget Constant Modulus algorithm (LS-DRMTCMA) and the Block RLS-Despread Respread Multitarget Array (Block RLS-DRMTA). Computer simulation in both the AWGN static channel and the dynamic channel is performed. The simulation results indicate that the AP-DRMTA has superior bit error rate performance.
The affine projection algorithm (APA), and the entire class of algorithms equivalent to APA, attempts to accelerate the convergence of the normalized least-mean-squares (NLMS) algorithm by adapting weights based on pa...
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The affine projection algorithm (APA), and the entire class of algorithms equivalent to APA, attempts to accelerate the convergence of the normalized least-mean-squares (NLMS) algorithm by adapting weights based on past input vectors in addition to the usual NLMS adaptation based on the current input vector. Before deriving a fast version of it, we review our generalized APA algorithm called NLMS with orthogonal correction factors (NLMS-OCF). NLMS-OCF provides complete flexibility in choosing the past input vectors. This flexibility provides improved convergence over the APA and its equivalents. A fast version of NLMS-OCF is then derived which uses a lattice-based forward-backward predictor. The significant convergence properties of NLMS-OCF are summarized. Simulation results that compare NLMS-OCF and APA are presented. Copyright (C) 2000 John Wiley & Sons, Ltd.
作者:
Ikeda, KKyoto Univ
Dept Syst Sci Grad Sch Informat Kyoto 6068501 Japan
The affineprojection (AP) and the block orthogonal projection (BOP) algorithms are known to have good convergence properties even when the input signal is correlated. However, their convergence rates are not elucidat...
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The affineprojection (AP) and the block orthogonal projection (BOP) algorithms are known to have good convergence properties even when the input signal is correlated. However, their convergence rates are not elucidated yet, since they are based on orthogonal projection. and are too complicated to be analyzed. In this paper, we first consider their geometrical view and derive their convergence rates for white signals. Moreover, we provide an approximation method to evaluate the convergence rate for cot-related signals and show the results which are confirmed by computer simulations. The results imply that the convergence rate of the BOP algorithm gets saturated as the block size increases. (C) 2002 Elsevier Science B.V. All rights reserved.
This paper presents a novel robust adaptive filtering scheme based on the interactive use of statistical noise information and the ideas developed originally for efficient algorithmic solutions to the convex feasibili...
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This paper presents a novel robust adaptive filtering scheme based on the interactive use of statistical noise information and the ideas developed originally for efficient algorithmic solutions to the convex feasibility problems. The statistical noise information is quantitatively formulated as stochastic property closed convex sets by the simple design formulae developed in this paper. A simple set-theoretic inspection also leads to an important statistical reason for the sensitivity to noise of the affine projection algorithm (APA). The proposed adaptive algorithm is computationally efficient and robust to noise because it requires only an iterative parallel projection onto a series of closed half spaces that are highly expected to contain the unknown system to be identified and is free from the computational load of solving a system of linear equations. The numerical examples show that the proposed adaptive filtering scheme realizes dramatically fast and stable convergence for highly colored excited speech like input signals in severe noise situations.
The normalized LMS (NLMS) algorithm has been successfully used in many system identification problems. However, the NLMS algorithm is known to exhibit low convergence speed especially when the input data covariance ma...
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ISBN:
(纸本)0780374029
The normalized LMS (NLMS) algorithm has been successfully used in many system identification problems. However, the NLMS algorithm is known to exhibit low convergence speed especially when the input data covariance matrix is ill-conditioned. In this paper, we consider a sub-optimal implementation of the affineprojection (AP) algorithm based on a prewithening mechanism, which renders the convergence characteristics less sensitive to the coloring of the input signal spectrum than is the case for the NLMS algorithm. Comparisons with the AP algorithm are given to validate our approach. Implementation details are discussed in the context of hands-free telephony where echo cancelling and speech coding algorithms are integrated on the same DSP board.
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