A well-designed Voice Activity Detection (VAD) front-end minimizes processing demands. Spiking Neural Networks (SNNs), a cutting-edge paradigm in brain-inspired computing, excel in energy efficiency ...

Inspired by biological brain neurons, the spiking neural network uses differential dynamics equations and spike information encoding methods to build computing node models in neural networks (Maass, ...

In our simulation, a spiking neural network model was used with the spike-timing dependent plasticity rule to explore the above neural dynamics. We controlled the number of inhibitory neurons and the ...

These occur fairly rarely, so the networks get by on much less energy." Developing artificial neural networks that also "spike" in this way is thus an important field in AI research. Neural networks ...

Abstract: Recently, spiking neural networks (SNNs) have demonstrated substantial potential in computer vision tasks. In this paper, we present an Efficient Spiking Deraining Network, called ESDNet.

Developing artificial neural networks that also "spike" in this way is thus an important field in AI research. Neural networks must be trained if they are to be capable of completing certain tasks.

The textbook meaning of an artificial neural network (ANN) is a deep learning model made up of neurons that emulate the structure of the human brain. These neurons are designed to mimic the way nerve ...

Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural ...