Daniel G. Tiglea

Reducing the Communication and Computational Cost of Random Fourier Features Kernel LMS in Diffusion Networks

Diffusion kernel algorithms are interesting tools for distributed nonlinear estimation. However, for the sake of feasibility, it is essential in practice to restrict their computational cost and the number of communications. In this paper, we propose a censoring algorithm for adaptive kernel diffusi…