Physics-informed AI learns local rules behind flocking and collective motion behaviors

Researchers at Seoul National University and Kyung Hee University report a framework to control collective motions, such as ring, clumps, mill, flock, by training a physics-informed AI to learn the ...
IEEE

A Nonlinear Compensation Scheme for High Baud Rate Assisted by Neural Network Based on First-Order and Second-Order Perturbation Theory

Abstract: In order to effectively suppress the performance degradation caused by the cumulative nonlinear impairments due to the higher transmission rate and larger transmission capacity of optical ...
Gut

AI-empowered human microbiome research

Recent advances in high-throughput microbiome profiling have generated expansive data sets that offer unprecedented ...
IEEE

Adaptive Neural Network Tracking Control for Nonstrict-Feedback Nonlinear Systems With States and Inputs Quantization

Abstract: It is a common control issue that the input signal of the system is quantized in the controller-to-actuator channel via the communication network, but few results are available in ...