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On Regularization in Adaptive Filtering
IEEE Transactions on Audio, Speech, and Language Processing, 2011Regularization plays a fundamental role in adaptive filtering. An adaptive filter that is not properly regularized will perform very poorly. In spite of this, regularization in our opinion is underestimated and rarely discussed in the literature of adaptive filtering. There are, very likely, many different ways to regularize an adaptive filter. In this
Jacob Benesty +2 more
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Proceedings. Second Annual Conference on Communication Networks and Services Research, 2004., 2004
We present a new spam filter which acts as an additional layer in the spam filtering process. This filter is based on what we call a representative vocabulary. Spam e-mails are divided into categories in which each category is represented by a set of tokens which form a representative text (RT).
L. Pelletier +2 more
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We present a new spam filter which acts as an additional layer in the spam filtering process. This filter is based on what we call a representative vocabulary. Spam e-mails are divided into categories in which each category is represented by a set of tokens which form a representative text (RT).
L. Pelletier +2 more
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Digital Signal Processing, 2005
This paper derives an adaptive coherence filter for canceling interference from a signal of interest whose power spectral density is symmetric. A basic property of the Fourier transform of real signals is that their spectra are Hermitian symmetric. This property is exploited to determine which part of a spectrum is interference and which part is the ...
Jeremy R. Waller, Gary D. Brushe
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This paper derives an adaptive coherence filter for canceling interference from a signal of interest whose power spectral density is symmetric. A basic property of the Fourier transform of real signals is that their spectra are Hermitian symmetric. This property is exploited to determine which part of a spectrum is interference and which part is the ...
Jeremy R. Waller, Gary D. Brushe
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Adaptive collaborative filtering
Proceedings of the 2008 ACM conference on Recommender systems, 2008We present a flexible approach to collaborative filtering which stems from basic research results. The approach is flexible in several dimensions: We introduce an algorithm where the loss can be tailored to a particular recommender problem. This allows us to optimize the prediction quality in a way that matters for the specific recommender system.
Markus Weimer +2 more
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Evolutionary Adaptive Filtering
1995Evolutionary algorithms have seen an ever increasing use in a variety of applications owing to their robustness and ease of implementation. This paper considers the performance of these algorithms when applied to adaptive filtering, with particular emphasis on the direct system modelling problem.
Djamel Ait-Boudaoud +2 more
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Adaptive communication filtering
IEEE Transactions on Information Theory, 1962This paper reports the results of a study of adaptive communication filtering. It is assumed that either the noise or the signal is completely unknown and only the spectrum or autocorrelation function of the other is known. it is desired to filter according to a mean-square error criteria.
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Overparametrization in adaptive filters
1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2002Adaptive filters can be made fault tolerant by overparametrization. Conditions are derived such that no deterioration is caused by the redundancy under fault-free operation and that the deterioration caused by weight failures is minimized.
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2010
AFSQP is a Sequential Quadratic Programming algorithm which obtains global convergence through an adaptive filter technique. This adaptivity is the major innovation in this work. The resulting algorithm can deal with constraints involving different length scales without requiring their normalization.
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AFSQP is a Sequential Quadratic Programming algorithm which obtains global convergence through an adaptive filter technique. This adaptivity is the major innovation in this work. The resulting algorithm can deal with constraints involving different length scales without requiring their normalization.
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Chandrasekhar adaptive regularizer for adaptive filtering
ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005Adaptivity, stability, fast initial convergence, and low complexity are contradictory exigences in adaptive filtering. The least-mean-squares (LMS) algorithms suffer from a slow initial convergence, and the fast recursive least-squares (RLS) ones present numerical stability problems.
Amrane Houacine, Guy Demoment
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1997
Adaptive infinite impulse response (IIR) filters are those in which the zeros and poles of the filter can be adapted. For that benefit the adaptive IIR filters usually have adaptive coefficients on the transfer function numerator and denominator. Adaptive IIR filters present some advantages as compared with the adaptive FIR filters, including reduced ...
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Adaptive infinite impulse response (IIR) filters are those in which the zeros and poles of the filter can be adapted. For that benefit the adaptive IIR filters usually have adaptive coefficients on the transfer function numerator and denominator. Adaptive IIR filters present some advantages as compared with the adaptive FIR filters, including reduced ...
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