Machine learning (ML) algorithms are key enablers to effectively assimilate and extract
information from many generated data in the Internet of Things. However, running ML …

A novel memristive synapse model based on the HP memristor is proposed in this paper,
which can address the problem of synaptic weight infinite modulations. The sliding threshold …

Astrocytes play a significant role in the working memory (WM) mechanism, yet their
contribution to spiking neuron-astrocyte networks (SNAN) is underexplored. This study …

The introduction of 5G communication capabilities presents additional challenges for the
development of products and services that can fully exploit the opportunities offered by high …

This case study provides feasibility analysis of adapting Spiking Neural Networks (SNN)
based Structural Health Monitoring (SHM) system to explore low-cost solution for inspection …

Network congestion is one of the critical reasons for degradation of data throughput
performance in Networks-on-Chip (NoCs), with delays caused by data-buffer queuing in …

Internet of Things (IoT) and Cyber-Physical Systems (CPS) have profoundly influenced the
way individuals and enterprises interact with the world. Although attacks on IoT devices are …

The paper presents a neuromorphic system implemented on a Field Programmable Gate
Array (FPGA) device establishing fault tolerance using a learning method, which is a …

Spike-based brain-inspired systems have shown an immense capability to achieve internal
stability, widely referred to as homeostasis. This ability enrols them as the best candidate for …

We present a novel methodology that addresses the problem of faults in synapses of a
spiking neural network using astrocyte regulation, inspired by recovery processes in the …