An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the tail end ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

In order to evaluate a dataset of over 11 million cells from a study of dengue fever, Yale researchers developed a cutting-edge neural network that recognizes and represents patterns in large datasets ...

When we design a skyscraper we expect it will perform to specification: that the tower will support so much weight and be able to withstand an earthquake of a certain strength. But with one of the ...

In a recent conversation with an expert in artificial intelligence (AI), specifically deep learning (DL), I was told that designing DL algorithms to map onto deep neural networks (DNN) is analogous to ...

Principal Research Fellow at AI and Cyber Futures Institute, Charles Sturt University Optical illusions, quantum mechanics and neural networks might seem to be quite unrelated topics at first glance.