While the recursive least square (RLS) algorithm is widely used in adaptive filtering applications like acoustic echo cancellation (AEC) due to its fast convergence rate, its high computational complexity severely limit its practical deployment for long filters. In this paper, a regularized block-diagonal RLS (RBD-RLS) algorithm is proposed to address these challenges. By approximating the inverse covariance matrix as a block-diagonal structure, RBD-RLS simplifies the update process into independent parallel computations of sub-blocks, effectively reducing the computational complexity. Additionally, Tikhonov regularization is applied to each sub-blocks for enhance numerical stability. A series of experimental results demonstrate that RBD-RLS maintains good convergence while significantly reducing computational complexity. Moreover, it still exhibits relative robustness in real-world scenarios.
Acoustic Echo Cancellation (AEC) remains a critical challenge in modern telecommunication systems and VoIP platforms. Traditional adaptive filtering algorithms, such as the Normalized Least Mean Squares (NLMS) and Recursive Least Squares (RLS), degrade significantly under non-linear loudspeaker distortions, severe doub...
Najeh Adam Farag· AlQalam journal of medical a...· 0 citations
Rotated-vector-sum (RVS) is widely used in multi-frequency distributed acoustic sensing (DAS), but its synthesis gain collapses in long-haul sensing or with large frequency intervals. To fundamentally elucidate this effect, we develop a theoretical model that separates the coherent and random contributions of the Rayle...
Noise reduction is crucial to improving real-time acoustic speech communication quality and intelligibility. We present a low-complexity adaptive noise cancellation system based on the Least Mean Squares (LMS) algorithm in a Digital Signal Processing (DSP) environment. The main objective of this research is to reduce t...
Mahesh Mudavath, Chiyttaveni Komaltha, K. S. Babu et al.· International journal of com...· 0 citations
This paper presents a scheme of Normalized Least Mean Square (NLMS) adaptive filters, implemented in time and frequency domains, for real-time Acoustic Echo Cancellation (AEC) applied on the embedded system, in this case is Raspberry Pi. Recognizing the inherent limitations of linear adaptive filtering in complex acous...
Ahmad Agus Setiawan, Naufal Ainur Rizal, Setya Widyawan Prakosa· International Conference on...· 0 citations
Most performance analysis of filtered-x least mean square (FxLMS) was involved with slow adaptation assumption. However, this assumption introduces analytical errors in the transient stage of the algorithm, especially for long secondary paths. This paper presents a detailed analysis
of single-frequency FxLMS algorithm...
Xiang-Ning Liao, Liang Yang, Xian-Wu Yang et al.· Noise Control Engineering Jo...· 0 citations
This work introduces a novel source separation and Carrier Frequency Offset (CFO) estimation method based on a semi-blind multi-modulus approach with embedded pilots for Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) communication systems. A hybrid cost function combining Least Sq...
K. Aliyu, Karim Abed-Meraim, A. Zerguine et al.· IEEE Open Journal of the Com...· 0 citations
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