With the continuous development of communication technology, the wireless communication
environment becomes more and more complex with various intentional and unintentional …

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 …

Feature engineering involves extracting information from raw-data to use in machine
learning or deep learning algorithms through feature transformation, feature generation or …

The growing prominence of spectrum sharing technologies has spurred interest in spectrum
monitoring technologies with the ability to identify unknown wireless signals. This paper …

In congested electromagnetic environments, cognitive radios require knowledge about other
emitters in order to optimize their dynamic spectrum access strategy. Deep learning …

In shared spectrum with multiple radio access technologies, wireless standard classification
is vital for applications such as dynamic spectrum access (DSA) and wideband spectrum …

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 …