Introducing ‘Neuromorphic Computing and Engineering’

Automotive Computing, Neuromorphic Computing, and Beyond

Welcome to 2018 and IEEE Micro’s 38th year. I’m delighted about last year’s issues. In addition to the traditional special issues on Hot Chips and Top Picks, we had special issues on cognitive architectures, architectures for the post-Moore era, Cool Chips and Hot Interconnects, and ultra-low-power processors. I deeply appreciate the efforts of everyone who reviewed the many articles submitted ...

Neuromorphic and biomorphic engineering systems

Neuromorphic and biomorphic engineering systems Many biological systems, from the molecular scale to the macroscale and from the body to the brain, display remarkable efficiency and robustness. For example, a single mammalian cell, approximately 10 micrometers in size, performs complex biochemical signal processing on its mechanical and chemical input signals with highly noisy and imprecise par...

Tutorial: Neuromorphic computing

Frontiers in Neuromorphic Engineering

Neurobiological processing systems are remarkable computational devices. They use slow, stochastic, and inhomogeneous computing elements and yet they outperform today’s most powerful computers at tasks such as vision, audition, and motor control, tasks that we perform nearly every moment that we are awake without much conscious thought or concern. Despite the vast amount of resources dedicated ...

ReRAM-Based Neuromorphic Computing

Artificial neural networks are currently being used as a promising means to solve problems in machine learning and computer science [1–3]. These networks are loosely inspired by massively parallel biological neural systems, but they are often implemented on mostly sequential hardware computing platforms, ignoring key features of real neural processing systems, such as their ability to carry out...