A signal-processing–based framework converts DNA sequences into numerical signals to identify protein-coding regions. By integrating spectral ...

Scientists in the US have created a tiny silicon chip that can perform mathematical ...

AI-native air interfaces represent a shift from mathematical models to learned representations at the PHY layer.

We’re honored to welcome Tom and Ram to our advisory board. Their combined insights, from standards in verification and ...

The conversation about 6G begins with familiar building blocks: Multiple-Input Multiple-Output (MIMO) and full duplex ...

Llyodstern, a technology-driven firm specializing in advanced market analytics, today announced the successful deployment of a real-time AI signal framework across its analytical platform, following ...

Trxdynis stated that the Q4 deployment also improves platform stability and scalability, allowing the system to process higher data volumes while maintaining consistent performance. These ...

For example, a Convolutional Neural Network (CNN) trained on thousands of radar echoes can recognize the unique spatial signature of a small metallic fragment, even when its signal is partially masked ...

A new Friedman IR-Loaded and Wampler Pedalhead are the first new products to benefit from the new tech ...

A new technical paper titled “A Survey on Acoustic Side-Channel Attacks: An Artificial Intelligence Perspective” was published by researchers at Penn State University. “Acoustic Side-Channel Attacks ...

Coarse-Grained Reconfigurable Arrays (CGRAs) have been in the academic world for decades ([1], [2]). They are considered ideal to accelerate compute-intensive Digital Signal Processing (DSP) and ...

Traditional signal processing techniques have achieved much, but they face notable limitations when confronted with complex, high-volume data. Classical methods often rely on manual feature extraction ...