The design and on-chip implementation of learning algorithms for neuromorphic spike domain memristive architectures is a challenging problem. In this chapter, we provide a short overview of the challenges, open problems, architectures and state of the art implementations of spike-based CMOS-memristive neural networks and systems. The importance of biomimicry, the feasibility of scalability, large-scale information processing, data rate challenges, and building a system of systems make this a vibrant topic for discussion.
|Original language||English (US)|
|Title of host publication||Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications|
|Number of pages||12|
|State||Published - Jan 1 2021|
Bibliographical notePublisher Copyright:
© 2021 Elsevier Inc. All rights reserved.
- Spiking neural network
ASJC Scopus subject areas
- Arts and Humanities(all)