Jul 14, 2022 · We propose the adaptive random Fourier features Gaussian kernel LMS (ARFF-GKLMS). Like most kernel adaptive filters based on stochastic gradient descent.
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Jul 14, 2022 · Like most kernel adap- tive filters based on stochastic gradient descent, this algorithm uses a preset number of random Fourier features to save.
The proposed adaptive random Fourier features Gaussian kernel LMS (ARFF-GKLMS) achieves a performance improvement in terms of convergence rate, ...
Like most kernel adaptive filters based on stochastic gradient descent, this algorithm uses a preset number of random Fourier features to save computation cost.
Algorithm and Architecture Design of Random Fourier Features-Based ...
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Dec 14, 2022 · Random Fourier features (RFF) facilitate the development of kernel adaptive filters with a fixed network structure. For the first time, this ...
In this work, we introduce the concept of nonlinear adaptive filtering of graph signals. Adaptive filtering in reproducing kernel Hilbert spaces (RKHS) has ...
Sep 10, 2024 · This work develops a diffusion kernel filtering algorithm based on the random Fourier approximation method.
The performance of kernel adaptive filtering algorithms (KAFs) with nonlinear recurrent structures surpasses traditional KAFs, attributed to the ...
Abstract: This work introduces kernel adaptive graph filters that operate in the reproducing kernel Hilbert space. We propose a centralized graph kernel ...
In this paper, we propose a censoring algorithm for adaptive kernel diffusion networks based on random Fourier features that locally adapts the number of nodes ...