LMS Adaptive Filters for Noise Cancellation: A Review

Dixit, Shubhra; Nagaria, Deepak

doi:10.11591/ijece.v7i5.pp2520-2529

Cited by 81 publications

(57 citation statements)

References 68 publications

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“…The following equations describes the LMS operation [22] (5) (6) 7Where, =array output, =input data vector, =reference signal, =weight vector, =error signal, and =step size ( , where is the largest Eigenvalue of correlation matrix as in (2) Any change to the input data characteristics require changing the filter weights to adapt to these changes. The target of the filter is that becomes zero [23,24]. The received signal at (m, n) th antenna for " m M, n N" , is represented by the following:…”

Section: Lmsmentioning

confidence: 99%

Hybrid MVDR-LMS beamforming for Massive MIMO

Tabra

Sabbar

2019

IJEECS

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<p>With the high speed of communication in LTE-5G, fast beamforming techniques need to be adopted. The training time required to form and steer the main lobes toward 5G multiple users must be short. Least-Mean-Square (LMS) training time is not suitable to work with in LTE-5G, but it has a good performance in forming multiple beams to large number of users and producing nulls in the interference direction. In this paper, an optimized hybrid MVDR-LMS beamforming algorithm is proposed to reduce the time required to estimate the antenna’s weights. This optimization is made by the benefit of previously set weights calculated using MVDR algorithms. The performance of the proposed hybrid MVDR-LMS algorithm tested using MATLAB 2016a.</p>

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Section: Lmsmentioning

confidence: 99%

Hybrid MVDR-LMS beamforming for Massive MIMO

Tabra

Sabbar

2019

IJEECS

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“…The weight update equation using Feintuch's LMS algorithm is + 1 = + @ * (10) Noise cancellation is one of the most important applications of adaptive filters, in which it desired to recover a useful signal, from a noisy one, + (Dixit, 2017;Lee, et al, 2017;Qureshi, et al, 2017). In adaptive noise cancellation, the noisy signal, + is employed as the reference signal for the adaptive filter whose input must be E , another version of the noise signal which is strongly correlated to as illustrated in Figure 2.…”

Section: ;mentioning

confidence: 99%

“…The least mean square (LMS) has been the traditional algorithm for adaptive filtering and has gained acceptability for hardware implementation by several researchers due to simple structure (Dixit, 2017), (Gupta & Beniwal, 2015). The main weakness of the conventional type LMS lies in its complexity in selectin.…”

Section: Introductionmentioning

confidence: 99%

Development of an Adaptive IIR Filter Based on Modified Robust Mixed-Norm Algorithm for Adaptive Noise Cancellation

2019

CEIS

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Noise cancellation is one of the most important applications of adaptive filters. The employment of adaptive filtering in most digital signal processing tasks is currently an area of growing interest as adaptive filters, due to their dynamic nature, perform better than the traditional filters in compensating for random noise in their environment. However, the compensation for impulsive interference or noise is desired since most adaptive algorithms earlier proposed modelled noise as a random process of the White Gaussian distribution. A modified robust mixed-norm (MRMN) algorithm recently proposed to compensate for impulsive interference has been found to be hardware efficient, however the MRMN algorithm has only been tested on adaptive FIR system identification task. In this paper, an adaptive IIR filter based on MRMN adaptive algorithm is proposed and tested for noise cancellation task. The developed filter structure was modelled and simulated in MATLAB environment. The results obtained showed that the MRMN algorithm does in fact compensate for the presence of impulsive interference, however, at a higher computational complexity relative to the LMS algorithm.

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“…Bu yöntemler içinde düşük hesaplama karmaşıklığına sahip olması, dayanıklılığı ve uygulanmasının kolay olmasından dolayı LMS yordamı en sıklıkla kullanılan yöntem olmuştur [12]. LMS yordamı kullanan ileri beslemeli AGK sisteminin blok diyagramı Şekil 1'de verilmiştir.…”

Section: Aktif Gürültü Kontrolüunclassified

“…Normalize LMS (NLMS), Sign-Error LMS, Sign-Data LMS ve Sign-Sign LMS bu yöntemlerin en bilinenleri arasındadır [12]. Benzetim ortamında, dişçi delgisi sesi için bu yöntemler denenmiş ve en iyi başarım NLMS yordamıyla elde edildiğinden bu çalışmada NLMS yönteminin gerçek hayata uyarlanmış şekli olan normalize FxLMS yordamı kullanılmıştır.…”

Section: şEkil 1: İleri Beslemeli Agk -Lmsunclassified

Dişçi Delgisi Gürültüsü için Aktif Gürültü Denetleyici Tasarımı ve Uygulaması

Kahraman¹,

Doǧan²

2018

deufmd

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Özet: Dişçi delgileri yüksek frekanslı, hastaları rahatsız eden ve gürültü olarak adlandırılabilecek bir ses çıkartırlar. Dişçi delgisi sesi, rahatsız edici olmasının yanı sıra insan sağlığı üzerinde olumsuz etkilere sahiptir, bu nedenle gürültü kontrol yöntemleriyle bastırılması gereklidir. Bu çalışmada dişçi delgi sesi, mikrofonlar, hoparlör ve sayısal işleme kartından oluşan bir Aktif Gürültü Kontrol (AGK) sistemiyle açık alanda bastırılmaya çalışılmıştır. Çalışma, kullanılan yordam ve yüksek frekanslı bir gürültünün AGK yöntemiyle açık alanda bastırılmaya çalışılması yönlerinden yazında yer alan AGK çalışmalarından farklılık göstermektedir. Uygulama sonuçlarına göre önerilen AGK sisteminin başarımı tatmin edicidir. Active Noise Controller Design and Implementation for Dental Drill NoiseKeywords Active Noise Control, Fx-LMS, Noise Reduction.Abstract: Dental drills produce a high frequency sound that disturbs the patients and can be called as noise. The sound of dentist drill is not only disturbing but also has adverse effects on human health so it is needed to be suppressed with noise control methods. In this study, the dentist drill noise has tried to be suppressed in open field with an Active Noise Control (ANC) system that consists of microphones, speaker and a digital signal processing card. The study differs from the ANC studies in the literature in terms of the algorithm used and the attempt to suppress a high frequency noise with ANC method in an open field. According to the implementation results, the performance of the proposed ANC system is satisfactory.

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LMS Adaptive Filters for Noise Cancellation: A Review

Cited by 81 publications

References 68 publications

Hybrid MVDR-LMS beamforming for Massive MIMO

Hybrid MVDR-LMS beamforming for Massive MIMO

Development of an Adaptive IIR Filter Based on Modified Robust Mixed-Norm Algorithm for Adaptive Noise Cancellation

Dişçi Delgisi Gürültüsü için Aktif Gürültü Denetleyici Tasarımı ve Uygulaması

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