Adaptive Composite Fixed-Time RL-Optimized Control for Nonlinear Systems and Its Application to Intelligent Ship Autopilot

Engineering, Mechanical Engineering, Ocean Engineering, Transportation Engineering, Electrical Engineering, Information Science, Computer Science, Automation, Artificial Intelligence,
adaptive control   fixed-time control   reinforcement learning   nonlinear systems   neural networks   intelligent ships   optimization methods  

Nonlinear Fixed-Time Reinforcement Learning Optimized Control for Intelligent Ship Autopilots In recent years, intelligent autopilot technology has gradually become a research hotspot in the field of automation control. For complex nonlinear systems, the design of optimized control strategies, especially the achievement of system stability and perf...

Policy Consensus-Based Distributed Deterministic Multi-Agent Reinforcement Learning

Engineering, Electrical Engineering, Information Science, Computer Science, Artificial Intelligence,
policy consensus   distributed algorithms   multi-agent reinforcement learning   deterministic policy gradient   directed graphs   continuous control   deep reinforcement learning  

Policy Consensus-Based Distributed Deterministic Multi-Agent Reinforcement Learning Research Report Reinforcement Learning (RL) has made significant breakthroughs in recent years in various fields such as robotics, smart grids, and autonomous driving. However, in real-world scenarios, multi-agent collaboration problems, also known as Multi-Agent Re...

Efficient CORDIC-based Activation Function Implementations for RNN Acceleration on FPGAs

Engineering, Electrical Engineering, Information Science, Electronic Information, Computer Science, Artificial Intelligence,
CORDIC   RNN   activation function   FPGA   hardware acceleration   natural language processing   edge devices  

Efficient Implementation of RNN Activation Functions: Breakthroughs in CORDIC Algorithms and FPGA Hardware Acceleration Background and Research Significance In recent years, with the rapid advancement of deep learning technologies, Recurrent Neural Networks (RNNs), particularly Long Short-Term Memory (LSTM) networks, have demonstrated powerful capa...

A Monolithic 3D IGZO-RRAM-SRAM-Integrated Architecture for Robust and Efficient Compute-in-Memory

Engineering, Electrical Engineering, Information Science, Computer Science, Semiconductors and Information Devices, Artificial Intelligence,
compute-in-memory   monolithic 3D   RRAM   IGZO   3D stacking   neural networks   system optimization  

Monolithic 3D IGZO-RRAM-SRAM Compute-in-Memory Architecture: A Breakthrough in Improving Neural Network Computation Efficiency Background and Research Motivation As neural networks (NNs) continue to find applications in artificial intelligence, traditional computing architectures struggle to meet their needs for energy efficiency, speed, and densit...

Surface Structural Changes in Silicone Rubber Due to Electrical Tracking

Chemistry, Polymer Chemistry, Materials Chemistry, Engineering, Electrical Engineering, Materials Science, Organic Polymeric Materials, Information Science, Computer Science,
silicone rubber   electrical insulators   tracking   ATR-FTIR spectroscopy   two-dimensional correlation spectroscopy   aging   surface roughness  

Cutting-Edge Scientific News: Research Reveals Degradation Mechanisms of Silicone Rubber under Electrical Tracking Background: Motivation and Challenges With the rapid development of power transmission and distribution systems, polymer composite insulators have gradually replaced traditional glass and ceramic insulators as the preferred materials f...