Motif-Topology and Reward-Learning Improved Spiking Neural Network for Efficient Multi-Sensory Integration
Author:
Affiliation:
1. Chinese Academy of Sciences,Institute of Automation,China
Funder
Chinese Academy of Sciences
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9745891/9746004/09746157.pdf?arnumber=9746157
Reference25 articles.
1. Behavioral Indices of Multisensory Integration: Orientation to Visual Cues is Affected by Auditory Stimuli
2. Information Processing Architecture of Functionally Defined Clusters in the Macaque Cortex
3. Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing
4. Training Deep Spiking Neural Networks Using Backpropagation
5. Error-backpropagation in temporally encoded networks of spiking neurons
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1. Categorization of Speech Frequency Following Responses to English Vowels;2023 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE);2023-09-24
2. Research Advances and New Paradigms for Biology-inspired Spiking Neural Networks;J ELECTRON INF TECHN;2023
3. Explaining cocktail party effect and McGurk effect with a spiking neural network improved by Motif-topology;Frontiers in Neuroscience;2023-03-20
4. Unsupervised and efficient learning in sparsely activated convolutional spiking neural networks enabled by voltage-dependent synaptic plasticity;Neuromorphic Computing and Engineering;2023-01-06
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