Mitra, Rangeet, Choi, Kwonhue, Bhatia, Vimal et Kaddoum, Georges.
2026.
« Stochastic gradient based concurrent criterion learning and parameter-estimation ».
Franklin Open, vol. 16.
Prévisualisation |
PDF
Kaddoum-G-2026-34290.pdf - Version publiée Licence d'utilisation : Creative Commons CC BY. Télécharger (943kB) | Prévisualisation |
Résumé
For parameter-estimation over non-Gaussian noise, several learning criteria have emerged, which are known for their hyperparameter dependence. This work proposes a random Fourier feature based online hyperparameter free criterion learning algorithm that comprehensively alleviates dependence on hyperparameter choices and learns the criterion by self-adapting to underlying noise. First, for this joint parameter and criterion estimation, dynamical equations for the proposed hyperparameter-free algorithm are derived. Next, regarding the convergence characteristics of the proposed joint hyperparameter free parameter and criterion learning, rigorous analytical results are presented. Finally, case-studies aligned with classical signal processing applications like channel-estimation and channel-equalization are provided for performance validation of the proposed algorithm, and to verify the derived convergence analysis through computer simulations.
| Type de document: | Article publié dans une revue, révisé par les pairs |
|---|---|
| Chercheur(-euse): | Chercheur(-euse) Kaddoum, Georges |
| Affiliation: | Génie électrique |
| Date de dépôt: | 04 sept. 2026 20:48 |
| Dernière modification: | 27 sept. 2026 16:21 |
| URI: | https://espace2.etsmtl.ca/id/eprint/34290 |
Actions (Authentification requise)
 |
Dernière vérification avant le dépôt |