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A Class of Affine Projection Algorithms
2011Affine projection algorithms (APAs) are very good candidates for echo cancellation. The two main reasons for that are: they may converge and track much faster than the NLMS algorithm and they can be efficient from an arithmetic complexity viewpoint. In this chapter, we derive some useful APAs for SAEC with the WL model.
Jacob Benesty +3 more
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A comparative survey of fast affine projection algorithms
Digital Signal Processing, 2018Abstract The affine projection (AP) algorithm is one of the most celebrated adaptive filtering algorithms, and it achieves a good tradeoff between the convergence rate and computational complexity. However, the complexity of the AP algorithm increases with the projection order.
Feiran Yang 0001, Jun Yang 0004
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Scheduled-Step-Size Affine Projection Algorithm
IEEE Transactions on Circuits and Systems I: Regular Papers, 2012An approach for scheduling the step sizes of an adaptive filter using the affine projection algorithm (APA) is proposed so that its mean-square deviation (MSD) learning curve can be guided along a pre-designed trajectory. This approach eliminates the parameter-tuning process and does not require estimating unmeasurable stochastic quantities ...
Chang Hee Lee, PooGyeon Park
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Regularization of the improved proportionate affine projection algorithm
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012In sparse adaptive filters, the adaptation gain is “proportionately” redistributed among all the coefficients, emphasizing the large ones in order to speed up their convergence. The improved proportionate affine projection algorithm (IPAPA) is a very attractive choice for echo cancellation, since it combines the good convergence features of the affine ...
Constantin Paleologu +2 more
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Adaptive combination of affine projection and NLMS algorithms
Signal Processing, 2014We propose a novel scheme for combining two adaptation terms of affine projection algorithms with different projection orders and step-sizes. The selection of the mixing parameter that determines the performance of the proposed combination scheme is derived by the largest decrease of the mean-square deviation.
Choi, JH, Kim, SH, Kim, SW
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A sparse block exact affine projection algorithm
IEEE Transactions on Speech and Audio Processing, 2002The so-called affine projection algorithm (APA) has become a popular method in adaptive filtering applications and fast versions of it have been developed previously, such as fast affine projection (FAP) and the frequency domain block exact fast affine projection (BEFAP).
Geert Rombouts, Marc Moonen
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Complex proportionate-type affine projection algorithms
2013 Asilomar Conference on Signals, Systems and Computers, 2013An extension of complex proportionate-type normalized least mean square algorithms is proposed and derived. This new algorithm called the complex proportionate-type affine projection algorithm helps the estimation of unknown impulse responses when the input signal is colored.
Kevin T. Wagner, Milos I. Doroslovacki
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A Variable Regularization Method for Affine Projection Algorithm
IEEE Transactions on Circuits and Systems II: Express Briefs, 2010The affine projection algorithm (APA) is a generalization of the normalized least mean square algorithm. We propose a variable regularization factor for the APA. Instead of the conventional assumption that the a posteriori error is zero, we incorporate the statistical characteristic of the noise into the adaptation process based on a system ...
Wutao Yin, Aryan Saadat Mehr
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Time-variant regularization in affine projection algorithms
2013 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2013We propose a time-variant regularization in affine projection algorithms, where we update the regularization parameter with a gradient method using a momentum term parametrized by a momentum rate. To further improve the convergence properties of the algorithm in transient stages while ensuring a small final misadjustment, we adaptively estimate the ...
Amadou Ba, Sean McKenna
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Kernel Affine Projection Algorithm
2015The unknown system to be identified by an adaptive filter is usually assumed to be a linear system. Based on this assumption, we model the unknown system by a linear filter. In reality, however, there are cases where a linear filter is inadequate. In spite of this problem, using a very general nonlinear filter is not a good idea.
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