Abstract Complex Ginzburg–Landau (CGL) equations serve as canonical models in a great
variety of physical settings, such as nonlinear photonics, dynamical phase transitions …

Neuromorphic circuits emulating the bio‐brain functionality via artificial devices have
achieved a substantial scientific leap in the past decade. However, even with the advent of …

Neuromorphic visual system with image perception, memory, and preprocessing functions is
expected to simulate basic features of the human retina. Organic optoelectronic synaptic …

Photosynaptic organic field‐effect transistors (OFETs) represent a viable pathway to develop
bionic optoelectronics. However, the high operating voltage and current of traditional …

Brain-inspired electronics require artificial synapses that have ultra-low energy
consumption, high operating speed, and stable flexibility. Here, we demonstrate a flexible …

Convolutional neural networks (CNNs) have gained much attention because they can
provide superior complex image recognition through convolution operations. Convolution …

Confronted by the difficulties of the von Neumann bottleneck and memory wall, traditional
computing systems are gradually inadequate for satisfying the demands of future data …

The memristor is a resistive switch where its resistive state is programable based on the
applied voltage or current. Memristive devices are thus capable of storing and computing …

The highly parallel artificial neural systems based on transistor‐like devices have recently
attracted widespread attention due to their high‐efficiency computing potential and the …

Artificial intelligence vision systems (AIVSs) with information sensing, processing, and
storage functions are increasingly gaining attention in the science and technology …