scholar.google.com › citations
This paper presents an adaptive filter which uses periodic fuzzy neural network (PFNN) to treat the equalization of nonlinear time-varying channels. The ...
It is known that the subband adaptive filter (SAF) structures increase the algorithmic convergence speed when the input signal involves the covariance matrix ...
Jan 1, 2023 · To accelerate the convergence speed of the functional link neural network (FLNN) particularly for colored input signals, this paper proposes a ...
In this paper, to improve the performance of the SSAF algorithm, we propose a new subband adaptive filter algorithm, which is derived by a normalized logarithm ...
This algorithm employs analysis filtering to divide the colored input signal into subband signals that approximate white noise [9], [10]. ... ...
This paper presents a new spline adaptive filtering (SAF) algorithm based on signed regressor (SR) of input signal. The algorithm is called SR-SAF ...
Oct 5, 2021 · In this paper, we focus on the distributed adaptive filtering algorithm and compare the DFair algorithm with the RDLMS, DNLMM, DGCLD, and DPLMS ...
Missing: Neural | Show results with:Neural
Oct 16, 2023 · One way to address this issue is to use nonlinear adaptive filters which incorporate nonlinearity in their model and thus improve the modelling ...
Missing: Subband | Show results with:Subband
People also ask
What is adaptive filter algorithm?
What is a functional link neural network?
Zhang, Subband adaptive filtering algorithm over functional link neural network, с. 1; Patel, Generalized soft-root-sign based robust sparsity-aware adaptive ...
Missing: Optimal | Show results with:Optimal
Sep 7, 2015 · An adaptive filter changes gain or feedback to optimally filter the signal. A non-adaptive filter is fixed at the point of time it is designed.