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
Proportionate Maximum Versoria Criterion-Based Adaptive Algorithm for Sparse System Identification
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems II: Express Briefs"
DOI: 10.1109/tcsii.2021.3123055
Abstract: Proportionate Maximum Versoria Criterion (P-MVC) based adaptive algorithms for unknown sparse system identification problem are proposed in this brief. The conventional proportionate type algorithms used for sparse system identification can work well only under Gaussian… read more here.
Keywords: sparse system; maximum versoria; system identification; algorithm ... See more keywords
Sparse System Identification of Leptin Dynamics in Women With Obesity
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Endocrinology"
DOI: 10.3389/fendo.2022.769951
Abstract: The prevalence of obesity is increasing around the world at an alarming rate. The interplay of the hormone leptin with the hypothalamus-pituitary-adrenal axis plays an important role in regulating energy balance, thereby contributing to obesity.… read more here.
Keywords: women obesity; sparse system; leptin; leptin cortisol ... See more keywords
Sparse-Aware Bias-Compensated Adaptive Filtering Algorithms Using the Maximum Correntropy Criterion for Sparse System Identification with Noisy Input
Sign Up to like & getrecommendations! Published in 2018 at "Entropy"
DOI: 10.3390/e20060407
Abstract: To address the sparse system identification problem under noisy input and non-Gaussian output measurement noise, two novel types of sparse bias-compensated normalized maximum correntropy criterion algorithms are developed, which are capable of eliminating the impact… read more here.
Keywords: system; sparse; noisy input; system identification ... See more keywords
A General Zero Attraction Proportionate Normalized Maximum Correntropy Criterion Algorithm for Sparse System Identification
Sign Up to like & getrecommendations! Published in 2017 at "Symmetry"
DOI: 10.3390/sym9100229
Abstract: A general zero attraction (GZA) proportionate normalized maximum correntropy criterion (GZA-PNMCC) algorithm is devised and presented on the basis of the proportionate-type adaptive filter techniques and zero attracting theory to highly improve the sparse system… read more here.
Keywords: sparse system; proportionate; zero attraction; pnmcc ... See more keywords