Sensitivity Analysis of RFML Applications

BP Muller, LJ Wong, AJ Michaels - IEEE Access, 2024 - ieeexplore.ieee.org
Performance of radio frequency machine learning (RFML) models for classification tasks
such as specific emitter identification (SEI) and automatic modulation classification (AMC) …

Temperature sensitivity of RFML algorithms

BE Olds, AJ Michaels - 2024 IEEE International Conference on …, 2024 - ieeexplore.ieee.org
A variety of hardware, including radios, are made to operate for extended periods of time in
extreme environments where temperatures can vary greatly. Both ambient temperature and …

An Analysis of Radio Frequency Transfer Learning Behavior

LJ Wong, B Muller, S McPherson… - Machine Learning and …, 2024 - mdpi.com
Transfer learning (TL) techniques, which leverage prior knowledge gained from data with
different distributions to achieve higher performance and reduced training time, are often …

Transferring Learned Behaviors between Similar and Different Radios

BP Muller, BE Olds, LJ Wong, AJ Michaels - Sensors, 2024 - mdpi.com
Transfer learning (TL) techniques have proven useful in a wide variety of applications
traditionally dominated by machine learning (ML), such as natural language processing …

Beyond Auto‐Models: Self‐Correlated Sui‐Model Respecifications

DA Griffith - Geographical Analysis, 2024 - Wiley Online Library
This year is the 50th anniversary of Besag's classic auto‐models publication, a cornerstone
in the development of modern‐day spatial statistics/econometrics. Besag struggled for …

Sensitivity Analysis of RFML-based SEI Algorithms

BE Olds - 2024 - vtechworks.lib.vt.edu
Abstract Radio Frequency Machine Learning (RFML) techniques for the classification tasks
of Specific Emitter Identification (SEI) and Automatic Modulation Classification (AMC) have …