Memristive Neuromorphics: Neuronal Emulators and Hardware Implementations of Neural Algorithms

Dear Colleagues,

In collaboration with the Journal of Low Power Electronics and Applications, we are bringing together a selected group of international experts to contribute to a Special Issue on “Memristive Neuromorphics: Neuronal Emulators and Hardware Implementations of Neural Algorithms”.

Many neuroscientists believe that brains differ from conventional computers in ways that exacerbate the dependence of algorithms on hardware. It is absurdly difficult, if not impossible, to understand cognition without considering its implementations. Fourteen years ago, HP Labs claimed the discovery of the memristor device, which has been regarded as one of the most appropriate neuromorphs for brain-inspired computing and bio-explainable artificial intelligence. Despite the enormous research interest in memristive neuromorphics and the many significant advances in this field, most observers would judge today’s memristive neuromorphic devices and circuits as still being in their infancy and lacking the sophistication and flexibility of their biological counterparts.

In this context, this Special Issue aims to bring together researchers working in directions including, but not limited to:

• Novel neuromorphic devices with new operating principles (not just new materials) that serve as the more compact and bio-realistic embodiments of neuronal elements.
• Novel neuromorphic devices or circuits for mimicking neuronal behaviors, especially those with a certain dynamic complexity.
• Novel neuromorphic devices or circuits for implementing neural algorithms beyond vector‐matrix multiplication.
• Device/circuit properties-inspired algorithms and their simulations or hardware implementations.

Dr. Huanglong Li
Prof. Dr. Si Wu
Guest Editors

Manuscript Submission Information

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