Automatic Gain Control

Automatic Gain Control (AGC) dynamically adjusts signal amplification to maintain a desired output level, addressing challenges in signal processing and control systems across diverse applications. Current research focuses on optimizing AGC algorithms for specific tasks, employing methods like gradient-free optimization, reinforcement learning, and neural operators to improve performance and adaptability in areas such as robotics, communication systems, and neural modeling. These advancements enhance robustness to noise and interference, improve control precision in robotic systems, and offer insights into biological signal processing mechanisms, leading to more efficient and adaptable systems.