An Efficient Proportionate Affine Projection Algorithm for Echo Cancellation

Abstract-The progressive increase of data rates in wireless communication systems has induced channel models with sampled impulse responses which are mostly sparse. This paper presents a unified derivation of adaptive filters exploiting sparsity in the complex domain, and compares the performance of classic and state-of-the-art adaptive algorithms for estimating sparse wireless channels as well as their tracking ability in this inherently time-varying environment. Simulation results confirm the efficiency of the sparsity-aware algorithms.

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“…Moreover, when the term αx(k)S (k)x H (k) is discarded, the SSM quasi NLMS (SSM-QNLMS) is unveiled [18]. 4 …”

Section: Penalty-based Algorithmsmentioning

confidence: 99%

“…The problem of echo cancellation is the original environment where those sparsity-aware algorithms have been applied [2] [3] [4].…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of adaptive filters for sparse wireless channel estimation

Lima

Ferreira

Martins

et al. 2017

2017 25th European Signal Processing Conference (EUSIPCO)

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“…Figure 2 illustrates the MSD curves of the classical APs and two SR-APs, i.e., SR-AP-1 and SR-AP-2, in the case of SNR = 30dB. For comparison purpose, the improved proportionate AP (IPAP) [6], [7] and variable step-size AP (VS-AP) [11] are considered. The parameters, α = −0.5 for the IPAP and C = 0.003 for the VS-AP, are chosen, respectively.…”

Section: The Measurement Noise V(i) Is Added To Y(i)the Mean Square mentioning

confidence: 99%

“…Examples include echo paths [4] and multipath wireless communication channels [5]. To address this issue, variants of the AP algorithm which employ the variable gain parameters in accordance with the magnitude of the filter weights have been presented [6], [7]. However, these proportionate AP algorithms do not exploit the sparsity condition of an underlying system to be identified.…”

Section: Introductionmentioning

confidence: 99%

Sparsity Regularized Affine Projection Adaptive Filtering for System Identification

Choi

2014

IEICE Trans. Inf. & Syst.

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Young-Seok CHOI †a) , Member SUMMARY A new type of the affine projection (AP) algorithms which incorporates the sparsity condition of a system is presented. To exploit the sparsity of the system, a weighted l 1 -norm regularization is imposed on the cost function of the AP algorithm. Minimizing the cost function with a subgradient calculus and choosing two distinct weightings for l 1 -norm, two stochastic gradient based sparsity regularized AP (SR-AP) algorithms are developed. Experimental results show that the SR-AP algorithms outperform the typical AP counterparts for identifying sparse systems. key words: system identification, adaptive filter, affine projection, sparsity, sparse system

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“…가 개발되었다 [6][7][8][9][10][11] . 기존 연구들이 효과적으로 반향을 제거하지만, 신 호 대 반향 비 (Signal to Echo Ratio, SER)가 -5 dB 이하 인 경우 대부분 좋은 성능을 보이지 않는다 [6][7][8][9][10][11] . [11] .…”

Section: 요인은 잡음이다 마이크에서 잡음을 제거하여 시스 템 사용자의 음성만을 깨끗하게 입력받기 위해unclassified

Robust End Point Detection for Robot Speech Recognition Using Double Talk Detection

Moon¹,

Park²,

Ko³

2012

The Journal of the Acoustical Society of Korea

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This paper presents a robust speech end-point detector using double talk detection in echoic conditioned speech recognition robot. The proposed method consists of combining conventional end-point detector result and double talk detector result. We have tested the proposed method in isolated word recognition system under echoic conditioned environment. As a result, the proposed algorithm shows superior performance of 30 % to the available techniques in the points of speech recognition rates.

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An Efficient Proportionate Affine Projection Algorithm for Echo Cancellation

Cited by 123 publications

References 9 publications

Performance evaluation of adaptive filters for sparse wireless channel estimation

Performance evaluation of adaptive filters for sparse wireless channel estimation

Sparsity Regularized Affine Projection Adaptive Filtering for System Identification

Robust End Point Detection for Robot Speech Recognition Using Double Talk Detection

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