Matrix computation, as a fundamental building block of information processing in science
and technology, contributes most of the computational overheads in modern signal …

Artificial intelligence (AI) is accelerating the development of unconventional computing
paradigms inspired by the abilities and energy efficiency of the brain. The human brain …

Reservoir computing offers a powerful neuromorphic computing architecture for
spatiotemporal signal processing. To boost the power efficiency of the hardware …

Neuromorphic computing aims at the realization of intelligent systems able to process
information similarly to our brain. Brain-inspired computing paradigms have been …

Complex-valued neural networks have many advantages over their real-valued
counterparts. Conventional digital electronic computing platforms are incapable of executing …

Convolutional neural networks, inspired by biological visual cortex systems, are a powerful
category of artificial neural networks that can extract the hierarchical features of raw data to …

Research in photonic computing has flourished due to the proliferation of optoelectronic
components on photonic integration platforms. Photonic integrated circuits have enabled …

Polariton lasers emit coherent monochromatic light through a spontaneous emission
process. As a rare example of a system in which Bose–Einstein condensation and …

In optical communication systems, fibre nonlinearity is the major obstacle in increasing the
transmission capacity. Typically, digital signal processing techniques and hardware are …

Reservoir computing is a highly efficient network for processing temporal signals due to its
low training cost compared to standard recurrent neural networks, and generating rich …