Zero-Attracting Kernel Maximum Versoria Criterion Algorithm for Nonlinear Sparse System Identification
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2022.3182139
Abstract: Sparsity-induced kernel adaptive filters have emerged as a promising candidate for a nonlinear sparse system identification (SSI) problem. The existing zero-attracting kernel least mean square (ZA-KLMS) algorithm relies on minimum mean square error criterion, which… read more here.
Keywords: sparse system; nonlinear sparse; algorithm; criterion ... See more keywords
A New Nonlinear Sparse Component Analysis for a Biologically Plausible Model of Neurons
Sign Up to like & getrecommendations! Published in 2019 at "Neural Computation"
DOI: 10.1162/neco_a_01214
Abstract: It is known that brain can create a sparse representation of the environment in both sensory and mnemonic forms (Olshausen & Field, 2004). Such sparse representation can be combined in downstream areas to create rich… read more here.
Keywords: new nonlinear; component; analysis; sparse component ... See more keywords