Stochasticity

Memristors Empower Spiking Neurons With Stochasticity

1 min read · Sun, Apr 26 2015

Circuits Spiking Neurons Stochasticity memristors

Maruan Al-Shedivat, et al., "Memristors empower spiking neurons with stochasticity." IEEE journal on Emerging and Selected Topics in Circuits and Systems 5 (2), 2015, 242. Abstract: Recent theoretical studies have shown that probabilistic spiking can be interpreted as learning and inference in cortical microcircuits. This interpretation creates new opportunities for building neuromorphic systems driven by probabilistic learning algorithms. However, such systems must have two crucial features: 1) the neurons should follow a specific behavioral model, and 2) stochastic spiking should be

Stochasticity Modeling in Memristors

1 min read · Tue, Apr 26 2016

Circuits Stochasticity memristors

Rawan Naous, et al., "Stochasticity modeling in memristors." IEEE Transactions on Nanotechnology 15 (1), 2016, 15. Abstract: Diverse models have been proposed over the past years to explain the exhibiting behavior of memristors, the fourth fundamental circuit element. The models varied in complexity ranging from a description of physical mechanisms to a more generalized mathematical modeling. Nonetheless, stochasticity, a widespread observed phenomenon, has been immensely overlooked from the modeling perspective. This inherent variability within the operation of the memristor is a vital