Optical signal processing has been playing a crucial part as powerful engine for various
information systems in the practical applications. In particular, achieving large-scale …

Integrated photonic devices and artificial intelligence have presented a significant
opportunity for the advancement of optical computing in practical applications. Optical …

On-chip photonic neural networks (PNN) are emerging as an attractive solution for artificial
neural networks due to their high computing density, low energy consumption, and compact …

Analog feature extraction (AFE) is an appealing strategy for low-latency and efficient
cognitive sensing systems since key features are much sparser than the Nyquist-sampled …

With the rapid development of the Internet of Things, how to efficiently store, transmit, and
process massive amounts of data has become a major challenge now. Optical neural …

The burgeoning of artificial intelligence has brought great convenience to people's lives as
large-scale computational models have emerged. Artificial intelligence-related applications …

摘要光学神经网络是区别于冯· 诺依曼计算架构的一种高性能新型计算范式, 具有低延时,
低功耗, 大带宽以及并行信号处理等优势. 片上集成是光学神经网络微型化发展的一种典型方式 …

Optical neural networks (ONNs) have gained significant attention due to their potential for
high-speed and energy-efficient computation in artificial intelligence. The implementation of …

Diffractive neural network in electromagnetic wave–driven system has attracted great
attention due to its ultrahigh parallel computing capability and energy efficiency. However …

Neuromorphic photonic computing has emerged as a competitive computing paradigm to
overcome the bottlenecks of the von-Neumann architecture. Linear weighting and nonlinear …