The human brain is a sophisticated, high‐performance biocomputer that processes multiple
complex tasks in parallel with high efficiency and remarkably low power consumption …

Improvements in computing performance have significantly slowed down over the past few
years owing to the intrinsic limitations of computing hardware. However, the demand for data …

Neuromorphic computing, inspired by the biological nervous system, has attracted
considerable attention. Intensive research has been conducted in this field for developing …

Neural networks have proven effective for solving many difficult computational problems, yet
implementing complex neural networks in software is computationally expensive. To explore …

Beyond-CMOS computational paradigms are necessary to solving the problems that we face
with modern computers in achieving scalability, low energy consumption, reduced latency …

Spiking neural network, inspired by the human brain, consisting of spiking neurons and
plastic synapses, is a promising solution for highly efficient data processing in neuromorphic …

Inspired by the principles of the biological nervous system, neuromorphic engineering has
brought a promising alternative approach to intelligence computing with high energy …

Spiking neural network (SNN) is promising but the development has fallen far behind
conventional deep neural networks (DNNs) because of difficult training. To resolve the …

Competitive‐learning‐based spiking neural networks are capable of rapid, highly accurate
pattern recognition with minimal data through denoising mechanisms provide by adaptive …

Neuromorphic computing, which relies on a combination of a large number of neurons
massively interconnected by an even larger number of synapses, has been actively studied …