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 …

Brain-inspired electronics represent a promising paradigm to resolve the energy and time
bottlenecks in conventional digital machines. Recent advances have spanned both …

As the research on artificial intelligence booms, there is broad interest in brain‐inspired
computing using novel neuromorphic devices. The potential of various emerging materials …

Conventional computing based on von Neumann architecture cannot satisfy the demands of
artificial intelligence (AI) applications anymore. Neuromorphic computing, emulating …

The demand for computing power has been increasing exponentially since the emergence
of artificial intelligence (AI), internet of things (IoT), and machine learning (ML), where novel …

Brain-inspired approaches can efficiently analyze the activities of biological neural networks
and solve computationally hard problems with energy efficiencies unattainable with von …

Neuromorphic computing has emerged as one of the most promising paradigms to
overcome the limitations of von Neumann architecture of conventional digital processors …

Neurobiological processing systems are remarkable computational devices. They use slow,
stochastic, and inhomogeneous computing elements and yet they outperform today's most …

Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices,
and models that contrast the pervasive von Neumann computer architecture. This …

Neuromorphic devices and systems have attracted attention as next-generation computing
due to their high efficiency in processing complex data. So far, they have been demonstrated …