Multifunctional neuromorphic devices to tackle complex tasks are highly desirable for the
development of artificial neural networks. Threshold switching (TS) memory, which exhibits …

Forecasting is one of the main topics in data mining or machine learning in which
forecasting, a group of data used, has a label class or target. Thus, many algorithms for …

In recent years, spiking neural networks (SNNs) have gained popularity as a biologically
plausible and energy-efficient alternative to artificial neural networks. Unlike non-spiking …

Recent advancement of deep learning has been elevated the multifaceted nature in various
applications of this field. Artificial neural networks are now turning into a genuinely old …

This paper proposes the Particle Swarm Optimization model for enhancing the performance
of an Artificial Neural Network. The learning process of Artificial Neural Network requires a …

Fault detection is the task of discovering patterns of a certain fault in industrial
manufacturing. Early detection of fault is an essential task in industrial manufacturing …

In contrast to the previous artificial neural networks (ANNs), spiking neural networks (SNNs)
work based on temporal coding approaches. In the proposed SNN, the number of neurons …

To improve the robustness of fuzzy clustering algorithm with quadratic polynomial as the
clustering center, a robust polynomial kernel-based fuzzy dual-local information clustering …

Inspired by the brain working mechanism, the spiking neural networks has proven the
capability of revealing significant association between different variables spike behavior …

Considering the high computational demands of most methods, using network
communication models to simulate the brain is a more economical way. However, despite …