In this paper, starting from a robust statistics (RS) adaptive approach presented in a previous work entitled the combined NLMS-Sign (CNLMS-S) adaptive filter, an automatic combination technique with similar performances is proposed. Thus, in order to obtain better performances in acoustic echo cancellation (AEC) setups than with the normalized least-mean square (NLMS) algorithm, in the CNLMS-S...

Two-dimensional (2D) adaptive filtering is a technique that can be applied to many image and signal processing applications. This paper extends the one-dimensional adaptive filter algorithms to 2D structure and the novel 2D adaptive filters are established. Based on this extension, the 2D variable step-size normalized least mean squares (2D-VSSNLMS), the 2D-VSS affine projection algorithms (2D-...

The outstanding performance recently reached by neural language models (NLMs) across many natural processing (NLP) tasks has steered the debate towards understanding whether NLMs implicitly learn linguistic competence. Probes, i.e., supervised trained using NLM representations to predict properties, are frequently adopted investigate this issue. However, it is still questioned if probing classi...

Least mean square-partial parallel interference cancelation (LMS-PPIC) is a partial interference cancelation using adaptive multistage structure in which the normalized least mean square (NLMS) adaptive algorithm is engaged to obtain the cancelation weights. The performance of the NLMS algorithm is mostly dependent to its step-size. A fixed and non-optimized step-size causes the propagation of ...

In this thesis, low-complexity adaptive filtering algorithms that exploit the sparsity of signals and systems are derived and investigated. Specifically, sparsity-aware normalized least-mean square and affine projection algorithms are developed based on the l1-norm incorporated to their cost function, which we term zero-attracting NLMS (ZA-NLMS) and zero-attracting APA (ZA-APA). These algorithm...

Abstract It is of great significance to locate faults quickly and accurately in power distribution system improve reliability recover quickly. With high positioning accuracy, strong anti-interference ability mountainous areas cities, the provide all-weather all-round services, BeiDou-3 (BD3) navigation satellite has broad application prospects systems. Using filtering principle normalized least...

In this paper, the Acoustic Echo Cancellation (AEC) are investigated by using Finite Impulse Responses Adaptive Filter with the analysis of Mean Square Error (MSE) and its convergence property. It is the result of a project in the course Fundamental of Signal Processing at Chongqing University of Posts and Telecommunications. It focuses on Normalized Least Mean Square (NLMS) algorithm of adapti...

This paper presents an echo suppression system that combines a linear acoustic canceller (AEC) with deep complex convolutional recurrent network (DCCRN) for residual suppression. The filter taps of the AEC are adjusted in subbands by using normalized sign-error least mean squares (NSLMS) algorithm. NSLMS is compared commonly-used (NLMS), and combination each proposed model studied. utilization ...

One of the most widely used gradient-based adaptation algorithms is the so called normalized least mean square (NLMS) algorithm. The rate of convergence, misadjustment and noise insensitivity of the NLMS-type algorithm depend on the proper choice of the step size parameter, which controls the weighting applied to each coefficient update. Different step size methods have been proposed to improve...

(ABSTRACT) Adaptive filtering techniques are used in a wide range of applications, including echo cancellation, adaptive equalization, adaptive noise cancellation, and adaptive beamforming. The performance of an adaptive filtering algorithm is evaluated based on its convergence rate, misadjustment, computational requirements, and numerical robustness. We attempt to improve the performance by de...