Biologically inspired spiking neural networks are increasingly popular in the field of artificial
intelligence due to their ability to solve complex problems while being power efficient. They …

Artificial neural network is a very important part in the new industry of artificial intelligence. In
China, there are many researches on artificial neural network and artificial intelligence are …

A novel method of using the spiking neural networks (SNNs) and the electroencephalograph
(EEG) processing techniques to recognize emotion states is proposed in this paper. Three …

The explosion of “big data” applications imposes severe challenges of speed and scalability
on traditional computer systems. As the performance of traditional Von Neumann machines …

We demonstrate supervised learning in Spiking Neural Networks (SNNs) for the problem of
handwritten digit recognition using the spike triggered Normalized Approximate Descent …

Emotion recognition still poses a challenge lying at the core of the rapidly growing area of
affective computing and is crucial for establishing a successful human–computer interaction …

Spiking neural networks (SNNs) receive trains of spiking events as inputs. In order to design
efficient SNN systems, real-valued signals must be optimally encoded into spike trains so …

Compared to the abilities of the animal brain, many Artificial Intelligence systems have
limitations which emphasise the need for a Brain-Inspired Artificial Intelligence paradigm …

A growing body of literature examining the neurocognitive processes of interpersonal
linguistic interaction indicates the emergence of neural alignment as participants engage in …

Spiking Neural Networks (SNNs), known for their potential to enable low energy
consumption and computational cost, can bring significant advantages to the realm of …