The representation of individual memories in a recurrent neural network can be efficiently differentiated using chaotic recurrent dynamics.

Abstract: Localizing more sources than sensors with a sparse linear array (SLA) has long relied on minimizing a distance between two covariance matrices and recent algorithms often utilize ...

Abstract: Computing-In-Memory (CIM) is widely applied in neural networks due to its unique capability to perform multiply-and-accumulate operations within a circuit array. This process directly ...