Improvement of the Simplified Fast Transversal Filter Type Algorithm for Adaptive Filtering

Arezki, Madjid; Benallal, Ahmed; Berkani, Daoud

doi:10.3844/jcssp.2009.347.354

Cited by 2 publications

(4 citation statements)

References 12 publications

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“…This Algorithm 2 is close to that proposed in [45][46][47], with the same differences as mentioned at the end of Algorithm 1 presentation. This Algorithm 2 is listed in Table V, and its computation complexity is given in Table VI.…”

Section: Lc1; T Lcnsupporting

confidence: 82%

“…We recall here that in [45][46][47], the authors proposed a comparable version to our Algorithm 1 with the same complexity (only in terms of multiplications). The differences between theses algorithms are as follows: (i) the proposed recursive relation of the likelihood variable .new/ L; t and (ii) the proposed periodic regularization of .new/ L; t that we propose in this paper.…”

Section: The Proposed Algorithmmentioning

confidence: 99%

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New efficient adaptive fast transversal filtering (FTF)‐type algorithms for mono and stereophonic acoustic echo cancelation

Djendi

2014

Adaptive Control & Signal

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This paper addresses the field of stereophonic acoustic echo cancelation (SAEC) by adaptive filtering algorithms. Recently, simplified versions of the fast transversal filter (SFTF)-type algorithm has been proposed. In this paper, we propose two major contributions. In the first contribution, we propose two new FTF-type algorithms with low complexity and good convergence speed characteristics. These two proposed algorithms are mainly on the basis of a forward prediction scheme to estimate the so called dual Kalman gain, which is inherent in the filtering part update. This computation complexity is achieved by the introduction of new relations for the computation of the likelihood variables that are simple and lead to further simplifications on the prediction part of the two proposed algorithms. In the second contribution, we propose to adapt then apply these four new SFTF-type algorithms, (the two proposed algorithms in this paper and their original versions) in the SAEC applications. A fair comparison of the proposed algorithms with the original SFTF and the normalized least mean square algorithms, in mono and SAEC applications, is presented. Copyright 274 M. DJENDI Recently, a different approach for the SAEC problems (inter-channel coherence, adaptive filter lengths, etc.) was proposed in [18,19] by using the widely linear model, which is assigned to the processing of noncircular complex valued signals. A new hybrid solution to the same problem that uses frequency shifts to improve the performance of the state-of-art solution based on addition of half-wave rectified signals is presented in [20]. The authors in [21] proposed a windowing frequency domain adaptive filter, and an up-sampling block transforms preprocessing, to solve these constraints. The proposed adaptive filter uses windowing functions with smooth cutoff property to reduce the spectral leakage during filter updating, so the utilization of the independent noise introduced by preprocessing in SAEC can be increased. The proposed preprocessing is operated in short blocks with low processing delay, and it uses frequency-domain up-sampling to meet the minimal block length requirement given by the band limit of simultaneous masking. Another very recent and novel approach to SAEC is proposed in [22] and based on a combination of psychoacoustic effects. The principle of the proposed structure is to use an approach based on the 'missing-fundamental' phenomenon at low frequencies (below 500 Hz) and a modified phase modulation approach at higher frequencies.A basic scheme for SAEC is given in Figure 1, where we illustrate the concept with a transmission room on the left and a receiving room on the right [16,17,23,24]. In Figure 1, when we generate a signal in the transmission room, the two microphones mic 1 and mic 2 receive two sorts of signals: (i) the direct source signal modified by the path g 1 (then received by mic 1 / and g 2 (then received by mic 2 /, respectively, and (ii) the existing diffuse noises n 1 and n 2 in the transmission room and received ...

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Section: Lc1; T Lcnsupporting

confidence: 82%

Section: The Proposed Algorithmmentioning

confidence: 99%

New efficient adaptive fast transversal filtering (FTF)‐type algorithms for mono and stereophonic acoustic echo cancelation

Djendi

2014

Adaptive Control & Signal

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“…2) Algorithms: The choice of algorithm dictates the computational cost and accuracy of the adaptive filter. The most common algorithm employed in adaptive filtering is the least mean-square (LMS) algorithm with a computational complexity of O(L) (L is the filter length) [55] and which has a weight update equation [56]…”

Section: A Adaptive Filteringmentioning

confidence: 99%

“…Another family of algorithms commonly used in adaptive filtering is based on the recursive least square (RLS) algorithm. This is a computationally more complex algorithm with a computational complexity of O(L 2 ) [55] and an update equation [57]…”

Section: A Adaptive Filteringmentioning

confidence: 99%

Artifact Removal in Physiological Signals—Practices and Possibilities

Sweeney

Ward

McLoone

2012

IEEE Trans. Inform. Technol. Biomed.

305

195

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The combination of reducing birth rate and increasing life expectancy continues to drive the demographic shift toward an aging population. This, in turn, places an ever-increasing burden on healthcare due to the increasing prevalence of patients with chronic illnesses and the reducing income-generating population base needed to sustain them. The need to urgently address this healthcare "time bomb" has accelerated the growth in ubiquitous, pervasive, distributed healthcare technologies. The current move from hospital-centric healthcare toward in-home health assessment is aimed at alleviating the burden on healthcare professionals, the health care system and caregivers. This shift will also further increase the comfort for the patient. Advances in signal acquisition, data storage and communication provide for the collection of reliable and useful in-home physiological data. Artifacts, arising from environmental, experimental and physiological factors, degrade signal quality and render the affected part of the signal useless. The magnitude and frequency of these artifacts significantly increases when data collection is moved from the clinic into the home. Signal processing advances have brought about significant improvement in artifact removal over the past few years. This paper reviews the physiological signals most likely to be recorded in the home, documenting the artifacts which occur most frequently and which have the largest degrading effect. A detailed analysis of current artifact removal techniques will then be presented. An evaluation of the advantages and disadvantages of each of the proposed artifact detection and removal techniques, with particular application to the personal healthcare domain, is provided.

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Improvement of the Simplified Fast Transversal Filter Type Algorithm for Adaptive Filtering

Cited by 2 publications

References 12 publications

New efficient adaptive fast transversal filtering (FTF)‐type algorithms for mono and stereophonic acoustic echo cancelation

New efficient adaptive fast transversal filtering (FTF)‐type algorithms for mono and stereophonic acoustic echo cancelation

Artifact Removal in Physiological Signals—Practices and Possibilities

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