An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...

UC Davis researchers have created a miniaturized microscope for real-time, high-resolution imaging of brain activity in mice.

What are convolutional neural networks in deep learning? Convolutional neural networks are used in computer vision tasks, which employ convolutional layers to extract features from input data.

Can a neural network be constructed entirely from DNA and yet learn in the same way as its silicon-based brethren? Recent ...

The core of quantum network research lies in efficiently and reliably establishing entanglement between nodes; however, the challenges of maintaining fragile quantum states are far more complex than ...

With artificial intelligence and machine learning (AI/ML) processors and coprocessors roaring across the embedded edge product landscape, the quest continues for high-performance technology that can ...

Dr. Geoffrey Hinton is a British-Canadian cognitive psychologist and computer scientist who won the Nobel Prize in Physics ...

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...

Digital transactions have emerged as a dominant force in today’s global commerce sector, empowering businesses and financial ...

Bankruptcy prediction has traditionally relied on statistical approaches such as Altman’s Z-score, which use financial ratios ...