Spiking neural networks (SNN), also often referred to as the third generation of neural
networks, carry the potential for a massive reduction in memory and energy consumption …

A large amount of red mud needs to be disposed of in China, which causes environmental
pollution. The feasibility of using red mud in autoclaved aerated concrete (AAC) has been …

Many methods and models have been proposed for solving difficult problems such as
prediction, planning and knowledge discovery in application areas such as bioinformatics …

Heart-rate estimation is a fundamental feature of modern wearable devices. In this paper we
propose a machine learning technique to estimate heart-rate from electrocardiogram (ECG) …

A dynamical system of spiking neurons with only feedforward connections can classify
spatiotemporal patterns without recurrent connections. However, the theoretical construct of …

The Support Vector Machine (SVM) classification algorithm, recently developed from the
machine learning community, was used to diagnose breast cancer. At the same time, the …

By adding different activation functions, a type of gradient-based neural networks is
developed and presented for the online solution of Lyapunov matrix equation. Theoretical …

As computational models inspired by the biological neural system, spiking neural networks
(SNN) continue to demonstrate great potential in the landscape of artificial intelligence …

In this paper, an adaptive trajectory tracking controller based on extended normalized radial
basis function network (ENRBFN) is proposed for 3-degree-of-freedom four rotor hover …

This paper shows that the heterogeneity in neuronal and synaptic dynamics reduces the
spiking activity of a Recurrent Spiking Neural Network (RSNN) while improving prediction …