Abstract
Memristors are an important emerging technology for memory and neuromorphic computing applications. In this chapter, we review the fundamentals of the memistor framework developed by Leon Chuan nearly 40 years ago, and examine resistive switching phenomena as the quintessential example of physical memristive systems. A special focus is given to the hardware emulation of biological synapses using memristors and groundbreaking results in the field are reviewed. Future research directions with spiking neural networks is outlined and the exciting prospect of emergent behavior in memristor networks is discussed.
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Notes
- 1.
The equation listed is for a charge-controlled memristor; [1] includes a definition for flux-controlled memristors as well.
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Sheridan, P., Lu, W. (2019). Memristors and Memristive Devices for Neuromorphic Computing. In: Chua, L., Sirakoulis, G., Adamatzky, A. (eds) Handbook of Memristor Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-76375-0_13
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