This paper provides amore biologically plausible evolutionary space by combining feedforward and feedback connections with excitatory and inhibitory neurons. We exploit the local spiking behavior of neurons to adaptively evolve neural circuits such as forward excitation,forward inhibition, feedback inhibition,...
We consider two biologically plausible structures, the Spiking Neural Network (SNN) and the self-attention mechanism. The former offers an energy-efficient and event-driven paradigm for deep learning, while the latter has the ability to capture feature dependencies, enabling Transformer to achieve ...
This paper introduces a method utilizing spiking neural networks (SNN) for learning, classification, and comparative analysis of brain data. As a case stud... MG Doborjeh,GY Wang,NK Kasabov,... - IEEE transactions on bio-medical engineering 被引量: 21发表: 2015年 A Hybrid Network Anomaly ...
In this paper, we present an alternative approach to perform spike sorting of complex brain signals based on spiking neural networks (SNN). The proposed architecture is suitable for hardware implementation by using resistive random access memory (RRAM) technology for the implementation of synapses whos...
In this paper, a work on spiking neural networks based on a model of a kind of Leaky Integrate-and-Fire (LIF) neuron with latency is presented. Efficient simulations are carried out through an ad hoc event-driven approach, highlighting some particular effects of synch rony in a simple feed...
In this paper, a binaural sound source lateralization spiking neural network (NN) will be presented which is inspired by most recent neurophysiological studies on the role of certain nuclei in the superior olivary complex (SOC) and the inferior colliculus (IC). The binaural sound source lateraliza...
In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, for financial time series prediction is introduced with the aim of exploiting the inherent temporal capabilities of the spiking neural model. The performance of the spiking neural networ...
The paper describes the integration of brain-inspired systems to perform audiovisual pattern recognition tasks. Individual sensory pathways as well as the integrative modules are implemented using a fast version of spiking neurons grouped in evolving spiking neural network (ESNN) architectures capable of...
Code Inference GitHub - Delver-of-Squeakrets/LISNN: Code for the model presented in the paper "LISNN: Improving Spiking Neural Networks with Lateral Interactions for Robust Object Recognition."github.com/Delver-of-Squeakrets/LISNN
This paper investigates Spiking Neural Networks (SNNs) applied as a novel tumour classification method. This paper will describe the creation of 3D tumour models, the generation of representative backscatter, the application of a feature extraction method and the use of SNNs to classify tumours as ...