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.

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 ...

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 ...

We’ve all come to terms with a neural network doing jobs such as handwriting recognition. The basics have been in place for years and the recent increase in computing power and parallel processing has ...

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.

Deep neural networks can perform wonderful feats, thanks to their extremely large and complicated web of parameters. But their complexity is also their curse: The inner workings of neural networks are ...