The volume, veracity, variability, and velocity of data produced from the ever increasing
network of sensors connected to Internet pose challenges for power management …

Neuromorphic computation is one of the axes of parallel distributed processing, and
memristor-based synaptic weight is considered as a key component of this type of …

The neuron models have been widely applied to neuromorphic computing systems and
chaotic circuits. However, discrete neuron models and their application in image encryption …

Nonvolatile memory (NVM)‐based neuromorphic computing has been attracting
considerable attention from academia and the industry. Although it is not completely …

Emerging memristive devices offer enormous advantages for applications such as non-
volatile memories and in-memory computing (IMC), but there is a rising interest in using …

In this article, we propose a novel chaotic neuron circuit with memristive neural synapses,
construct an architecture of memristive chaotic neural network (MCNN) and implement …

Oscillatory Neural Networks (ONNs) are currently arousing interest in the research
community for their potential to implement very fast, ultra-low-power computing tasks by …

Abstract The FitzHugh-Nagumo (FHN) spiking model has rich dynamics behaviors and can
imitate the firing process of a neuron. The memristor is a nonvolatile and resistance tunable …

Neuromorphic systems consisting of artificial neurons and synapses can process complex
information with high efficiency to overcome the bottleneck of von Neumann architecture …

In designing neuromorphic circuits and systems, developing compact and energy-efficient
neuron and synapse circuits is essential for high-performance on-chip neural architectures …