Abstract
Binary classification of high-dimensional, low-sample-sized atasets is feasible with channelized quadratic observers. Channel solutions can be optimized iteratively. A semi-supervised extension is developed for unlabeled data with smaller quantities of labeled data.
| Original language | English (US) |
|---|---|
| State | Published - 2024 |
| Event | 2024 Latin America Optics and Photonics Conference, LAOP 2024 - Puerto Vallarta, Mexico Duration: Nov 10 2024 → Nov 14 2024 |
Conference
| Conference | 2024 Latin America Optics and Photonics Conference, LAOP 2024 |
|---|---|
| Country/Territory | Mexico |
| City | Puerto Vallarta |
| Period | 11/10/24 → 11/14/24 |
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Electronic, Optical and Magnetic Materials
- Atomic and Molecular Physics, and Optics