Multiplicative analog frequency transform optical neural network encodes data in the frequency domain to perform matrix-vector products.
A configurable accelerator framework routes data streams between convolution accelerators and DSP clusters to perform efficient neural network operations.
An integrated circuit applies an aperture function to input data streams ordered row by row.
A noise leveraging method generates a low-rank matrix from neuromorphic device covariance to adjust neural network weights.
A runtime predictor generates simplified outputs to identify salient neural network computations.
Neural memory networks segment and nest data layers to reduce redundant storage while maintaining high capacity for IoT edge devices.