The Gauss-Seidel pseudo affine projection algorithm and its application for echo cancellation (original) (raw)
Robust variable step-size affine projection algorithm suitable for acoustic echo cancellation
The affine projection algorithm (APA) and different versions of it have proved to be very attractive choices for acoustic echo cancellation (AEC). In this context, a classical APA with a constant step-size has to compromise between two performance criteria, i.e., 1) high convergence rates and good tracking capabilities, and 2) low misadjustment and robustness against background noise variations and doubletalk. Consequently, a variable step-size APA (VSS-APA) is a more reliable solution. In this paper we propose a VSS-APA that is designed to recover the near-end signal from the error signal of the adaptive filter. Therefore, it is robust against near-end signal variations, including double-talk. Moreover, since it does not require a priori information about the acoustic environment, the proposed algorithm is easy to control in real-world AEC applications.
Set-membership affine projection algorithm for echo cancellation
This paper proposes a new data-selective affine projection algorithm for echo cancellation. The algorithm generalizes the concepts of the conventional set-membership affine-projection by incorporating a lower bound on the output error in order to prevent undesirable attenuation of the far-end signal. It is shown that the echo signal can more reliably be removed from the far-end user signals by employing the new algorithm in double talk situations. In addition, the proposed algorithm retains the fast convergence of the conventional SM-AP algorithm while keeping a reduced number of coefficient updates. Simulation results, using the ITU-T G.168 recommendation setup parameters, are presented in order to confirm the good features of the proposed algorithm.
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2007
We propose a gradient-limited affine projection algorithm (GL-APA), which can achieve fast and double-talk-robust convergence in acoustic echo cancellation. GL-APA is derived from the M-estimationbased nonlinear cost function extended for evaluating multiple error signals dealt with in the affine projection algorithm (APA). By considering the nonlinearity of the gradient, we carefully formulate an update equation consistent with multiple input-output relationships, which the conventional APA inherently satisfies to achieve fast convergence. We also newly introduce a scaling rule for the nonlinearity, so we can easily implement GL-APA by using a predetermined primary function as a basis of scaling with any projection order. This guarantees a linkage between GL-APA and the gradientlimited normalized least-mean-squares algorithm (GL-NLMS), which is a conventional algorithm that corresponds to the GL-APA of the first order. The performance of GL-APA is demonstrated with simulation results.
IEEE Signal Processing Letters, 2000
A straightforward generalization of the so-called affine projection algorithm (APA) to the multichannel (MC) case is easily obtained. However, due to the strong correlation between the input signals of the various channels, the resulting algorithm converges very slowly. This letter describes the way to overcome this problem and derives an efficient algorithm that turns out to make use of additional orthogonal projections.
Regularization of the Affine Projection Algorithm
IEEE Transactions on Circuits and Systems II: Express Briefs, 2000
The affine projection algorithm (APA) is an attractive choice for echo cancellation, mainly for its convergence features. A matrix inversion is required within the APA. For practical reasons, this matrix needs to be regularized, i.e., a positive constant is added to the elements of its main diagonal. This regularization parameter is of great importance in practice since, if it is not chosen properly, the APA may never converge, especially under low-signal-to-noise-ratio conditions. In this brief, we propose a formula for choosing the value of the regularization parameter, aiming at attenuating the effects of the noise in the adaptive filter estimate. Simulations performed in an acoustic echo cancellation scenario prove the validity of the approach in different noisy environments.
FPGA implementation of an efficient proportionate affine projection algorithm for echo cancellation
2011
This paper presents a field-programmable gate array (FPGA) implementation of a low-complexity proportionate affine projection algorithm (PAPA), in the context of echo cancellation. The proposed algorithm results as a combination between the recently developed “memory”-improved PAPA (MIPAPA) and a dichotomous coordinate descent (DCD) method. The MIPAPA takes into account the “history” of the proportionate factors, which is not the case for the classical PAPAs. Moreover, it achieves a lower computational complexity due to a recursive implementation of the “proportionate history;” as a consequence, the matrix that has to be inverted within the MIPAPA has the time-shift property, which can also lower the complexity. Concerning this task, the DCD technique efficiently performs the matrix inversion, requiring only addition operations. The proposed hardware implementation scheme takes advantage of the algorithm's specific features. The overall performance of the proposed DCD-MIPAPA ind...
A robust proportionate affine projection algorithm for network echo cancellation
2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100)
Echo cancelers which cover longer impulse responses (2 64 ms) are desirable. Long responses create a need for more rapidly converging algorithms in order to meet the specifications for network echo cancelers devised by ITU (International Telecommunication Union). In general, faster convergence implies a higher sensitivity to near-end disturbances, especially "double-talk." Recently, a fast converging algorithm called Proportionate NLMS (Normalized Least Mean Squares) algorithm (PNLMS) has been proposed. This algorithm exploits the sparseness of the echo path in order to increase the convergence rate. A robust version of PNLMS has also been presented which combines a double-talk detector with techniques from robust statistics to make the algorithm insensitive to double-talk. This paper presents a generalization of the robust PNLMS algorithm to a robust Proportionate Affine Projection Algorithm (APA) called PAPA that converges very fast.
This paper presents a field-programmable gate array (FPGA) implementation of a recently proposed variable stepsize affine projection algorithm (VSS-APA), in the context of acoustic echo cancellation. The proposed hardware implementation scheme takes advantage of the algorithm's specific features. Area and speed results are provided for the Xilinx Virtex 5 XC5VFX70T chip from the Xilinx ML507 evaluation board, when considering the particular case of the projection order p = 2. The overall performance of this acoustic echo canceller (AEC) indicates that it could be a reliable solution for real-world acoustic echo cancellation scenarios.
The Gauss-Seidel fast affine projection algorithm
… Systems, 2002.(SIPS'02). …, 2002
In this paper we propose a new stable Fast Affine Projection algorithm based on Gauss-Seidel iterations (GSFAP). We investigate its implementation using the logarithmic number system (LNS) and compare it with two other fast affine projection (FAP) algorithms. Simplified and multi-input GSFAP versions are also proposed. We show that the algorithm is only marginally more complex than NLMS and simpler than other FAP algorithms. Its application for acoustic echo cancellation is also investigated.
A practical solution for the regularization of the affine projection algorithm
2014 10th International Conference on Communications (COMM), 2014
The regularization of the affine projection algorithm (APA) is of great importance in echo cancellation applications. The regularization parameter, which depends on the level of the near-end signal, is added to the main diagonal of the input signal correlation matrix to ensure the stability of the APA. In this paper, we propose a practical way for evaluating the power of the near-end signal or, equivalently, the signal-to-noise ratio that is explicitly related to the regularization parameter. Simulation results obtained in the context of acoustic echo cancellation support the appealing performance of the proposed solution.