TOPS-speed complex-valued convolutional accelerator for feature extraction and inference.

ABSTRACT: Complex-valued neural networks process both amplitude and phase information, in contrast to conventional artificial neural networks, achieving additive capabilities in recognizing phase-sensitive data inherent in wave-related phenomena. The ever-increasing data capacity and network scale place substantial demands on underlying computing hardware. In parallel with the successes and extensive efforts made in electronics, optical neuromorphic hardware is promising to achieve ultra-high computing performances due to its inherent analog architecture and wide bandwidth. Here, we report a complex-valued optical convolution accelerator operating at over 2 Tera operations per second (TOPS). With appropriately designed phasors we demonstrate its performance in the recognition of synthetic aperture r

SUBMITTER: Bai Y 

PROVIDER: S-EPMC11697240 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature