A new technical paper titled “Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware” was published by researchers at Purdue University, Pennsylvania State ...

Training algorithm breaks barriers to deep physical neural networks. ScienceDaily . Retrieved June 2, 2025 from www.sciencedaily.com / releases / 2023 / 12 / 231207161444.htm ...

By using a neural network-based decoupling algorithm, the team was able to resolve spectral interference within the existing system, reducing both the complexity and cost of the design.

Researchers at Soongsil University (Korea) published “A Survey on Efficient Convolutional Neural Networks and Hardware Acceleration.” Abstract: “Over the past decade, deep-learning-based ...

Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...

The design of metasurface-based devices with high-accuracy functionalities is significantly desirable. Towards this goal, Scientist in China propose a bidirectional deep neural network combined ...

After assessing several classification algorithms, MIA3G was trained on neural networks with the most balanced performance and then tested on a heterogeneous cohort. The model was optimized to reduce ...