Researchers at University of Jyväskylä (Finland) advance understanding of gold nanocluster behavior at elevated temperatures ...

A new publication from Opto-Electronic Technology; DOI   10.29026/oet.2025.250010, discusses how a photonic vibration ...

Artificial intelligence is reshaping cybersecurity, but much of that progress has focused on cloud and enterprise ...

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 ...

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 ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

Abstract: Computing matrix gradient has become a key aspect in modern signal processing/machine learning, with the recent use of matrix neural networks requiring matrix backpropagation. In this field, ...