Autonomous Learning of Attractors in Neuromorphic Computing with Wien Bridge Oscillators

This research explores a novel approach to neuromorphic computing by leveraging the dynamics of Wien bridge oscillators for autonomous learning. The study's potential lies in creating more energy-efficient and biologically-inspired computing systems.

• •Focuses on neuromorphic computing, aiming for brain-like computation.
• •Utilizes Wien bridge oscillator networks for attractor learning.
• •Potentially leads to advancements in energy-efficient AI hardware.