Frontiers

Robust Neuromorphic Computation Under Device Variability and Non-Idealities

Neuromorphic engineering draws inspiration from biological neural systems, which operate robustly despite significant variability, noise, and heterogeneity ...
AlphaGalileo

Neural-Network Switching Control Boosts High-Speed Nano-Positioning Accuracy

Struggling with hysteresis and slow computing in high-speed nano-positioning systems? A new study in Engineering presents a ...
Live Science

'Thermodynamic computer' can mimic AI neural networks — using orders of magnitude less energy to generate images

Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require. When you purchase through links on our site, we may earn an affiliate ...
IEEE

Adaptive PID Gain Scheduling Control for Hydropower Turbine Using Neural CDE and Stochastic Distribution Shaping

Abstract: This paper introduces a gain-scheduling PID controller design strategy for hydroturbine frequency control mode. This scheme first uses real data to learn the nonlinear dynamics of the ...
C&EN

Mode Visualization and Control of Complex Lasers Using Neural Networks

Blackett Laboratory, Department of Physics, Imperial College London, London SW7 2BW, U.K. Blackett Laboratory, Department of Physics, Imperial College London, London ...