5 papers
Self-Organized Learning in Oscillatory Neural Networks with Memristive Signed Couplings
Riley Acker, Aman Desai, Garrett Kenyon +1
Oscillatory neural networks (ONNs) have emerged as a promising neuromorphic architecture, leveraging coupled dynamical systems to perform computation and represent information thro…
How to Train Your Resistive Network: Generalized Equilibrium Propagation and Analytical Learning
Jonathan Lin, Aman Desai, Frank Barrows +1
Machine learning is a powerful method of extracting meaning from data; unfortunately, current digital hardware is extremely energy-intensive. There is interest in an alternative an…
Autonomous Learning of Attractors for Neuromorphic Computing with Wien Bridge Oscillator Networks
Riley Acker, Aman Desai, Garrett Kenyon +1
We present an oscillatory neuromorphic primitive implemented with networks of coupled Wien bridge oscillators and tunable resistive couplings. Phase relationships between oscillato…
A unifying approach to self-organizing systems interacting via conservation laws
Frank Barrows, Guanming Zhang, Satyam Anand +5
We present a unified framework for embedding and analyzing dynamical systems using generalized projection operators rooted in local conservation laws. By representing physical, bio…
Learning Personal Food Preferences via Food Logs Embedding
Ahmed A. Metwally, Ariel K. Leong, Aman Desai +3
Diet management is key to managing chronic diseases such as diabetes. Automated food recommender systems may be able to assist by providing meal recommendations that conform to a u…