While deep machine learning technologies are now pervasive in state-of-the-art image
recognition and natural language processing applications, only in recent years have these …

Applications of machine learning are subject to three major components that contribute to
the final performance metrics. Within the category of neural networks, and deep learning …

This paper presents a comprehensive framework for generating radio frequency (RF)
datasets, designing deep learning (DL) detectors, and evaluating their detection …

The frequency-hopping spread spectrum (FHSS) technique is widely used in secure
communications. In this technique, the signal carrier frequency hops over a large band. The …

As one of the most widely used spread spectrum techniques, the frequency-hopping spread
spectrum (FHSS) has been widely adopted in both civilian and military secure …

直接序列扩频(Direct Sequence Spread Spectrum, DSSS) 信号的宽频带特性所带来的高采样
率增加了参数估计的实现难度. 针对现有技术所面临的问题与挑战, 融合压缩采样与深度神经 …

While the toolset known as Machine Learning (ML) is not new, several of the tools available
within the toolset have seen revitalization with improved hardware, and have been applied …

Previous research on frequency hopping (FH) signal recognition utilizing deep learning only
focuses on single-label signal, but can not deal with overlapped FH signal which has multi …

This article presents a customized approach for training a supervised learning neural
network with the adaptive moment estimation algorithm, to classify the number of frequency …

A frequency hopping orthogonal frequency division multiple access (FH-OFDMA) can
provide low probability of detection (LPD) and anti-jamming capabilities to users against …