Cargando…

BSNN: Towards faster and better conversion of artificial neural networks to spiking neural networks with bistable neurons

The spiking neural network (SNN) computes and communicates information through discrete binary events. Recent work has achieved essential progress on an excellent performance by converting ANN to SNN. Due to the difference in information processing, the converted deep SNN usually suffers serious per...

Descripción completa

Detalles Bibliográficos
Autores principales:	Li, Yang, Zhao, Dongcheng, Zeng, Yi
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2022
Materias:	Neuroscience
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9597447/ https://www.ncbi.nlm.nih.gov/pubmed/36312025 http://dx.doi.org/10.3389/fnins.2022.991851

Ejemplares similares

Classifying the Perceptual Interpretations of a Bistable Image Using EEG and Artificial Neural Networks
por: Hramov, Alexander E., et al.
Publicado: (2017)

Bistable Firing Pattern in a Neural Network Model
por: Protachevicz, Paulo R., et al.
Publicado: (2019)

Implementing Signature Neural Networks with Spiking Neurons
por: Carrillo-Medina, José Luis, et al.
Publicado: (2016)

Comparison of Artificial and Spiking Neural Networks on Digital Hardware
por: Davidson, Simon, et al.
Publicado: (2021)

Predicting Spike Features of Hodgkin-Huxley-Type Neurons With Simple Artificial Neural Network
por: Wang, Tian, et al.
Publicado: (2022)

Brain-inspired neural circuit evolution for spiking neural networks
por: Shen, Guobin, et al.
Publicado: (2023)

GLSNN: A Multi-Layer Spiking Neural Network Based on Global Feedback Alignment and Local STDP Plasticity
por: Zhao, Dongcheng, et al.
Publicado: (2020)

A Functional Spiking Neural Network of Ultra Compact Neurons
por: Stoliar, Pablo, et al.
Publicado: (2021)

Toward Reflective Spiking Neural Networks Exploiting Memristive Devices
por: Makarov, Valeri A., et al.
Publicado: (2022)

Neural Networks for Modeling Neural Spiking in S1 Cortex
por: Lucas, Alice, et al.
Publicado: (2019)

STNet: A novel spiking neural network combining its own time signal with the spatial signal of an artificial neural network
por: Liu, Fang, et al.
Publicado: (2023)

Neuronal-Plasticity and Reward-Propagation Improved Recurrent Spiking Neural Networks
por: Jia, Shuncheng, et al.
Publicado: (2021)

Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks
por: de Santos-Sierra, Daniel, et al.
Publicado: (2015)

Integrating Non-spiking Interneurons in Spiking Neural Networks
por: Strohmer, Beck, et al.
Publicado: (2021)

SpikePropamine: Differentiable Plasticity in Spiking Neural Networks
por: Schmidgall, Samuel, et al.
Publicado: (2021)

Phase diagram of spiking neural networks
por: Seyed-allaei, Hamed
Publicado: (2015)

Linear leaky-integrate-and-fire neuron model based spiking neural networks and its mapping relationship to deep neural networks
por: Lu, Sijia, et al.
Publicado: (2022)

Response Dynamics in an Olivocerebellar Spiking Neural Network With Non-linear Neuron Properties
por: Geminiani, Alice, et al.
Publicado: (2019)

Sharing leaky-integrate-and-fire neurons for memory-efficient spiking neural networks
por: Kim, Youngeun, et al.
Publicado: (2023)

Multisensory Concept Learning Framework Based on Spiking Neural Networks
por: Wang, Yuwei, et al.
Publicado: (2022)

SpykeTorch: Efficient Simulation of Convolutional Spiking Neural Networks With at Most One Spike per Neuron
por: Mozafari, Milad, et al.
Publicado: (2019)

Backpropagation with biologically plausible spatiotemporal adjustment for training deep spiking neural networks
por: Shen, Guobin, et al.
Publicado: (2022)

A Curiosity-Based Learning Method for Spiking Neural Networks
por: Shi, Mengting, et al.
Publicado: (2020)

Plasticity in memristive devices for spiking neural networks
por: Saïghi, Sylvain, et al.
Publicado: (2015)

Sparse Computation in Adaptive Spiking Neural Networks
por: Zambrano, Davide, et al.
Publicado: (2019)

Quantization Framework for Fast Spiking Neural Networks
por: Li, Chen, et al.
Publicado: (2022)

Trainable quantization for Speedy Spiking Neural Networks
por: Castagnetti, Andrea, et al.
Publicado: (2023)

Emotional brain network decoded by biological spiking neural network
por: Xu, Hubo, et al.
Publicado: (2023)

Distinctive properties of biological neural networks and recent advances in bottom-up approaches toward a better biologically plausible neural network
por: Jeon, Ikhwan, et al.
Publicado: (2023)

Recurrent Spiking Neural Network Learning Based on a Competitive Maximization of Neuronal Activity
por: Demin, Vyacheslav, et al.
Publicado: (2018)

Probabilistic Spike Propagation for Efficient Hardware Implementation of Spiking Neural Networks
por: Nallathambi, Abinand, et al.
Publicado: (2021)

Supervised Learning With First-to-Spike Decoding in Multilayer Spiking Neural Networks
por: Gardner, Brian, et al.
Publicado: (2021)

Corrigendum: A Curiosity-Based Learning Method for Spiking Neural Networks
por: Shi, Mengting, et al.
Publicado: (2020)

Editorial: Artificial Neural Networks as Models of Neural Information Processing
por: van Gerven, Marcel, et al.
Publicado: (2017)

Brian: A Simulator for Spiking Neural Networks in Python
por: Goodman, Dan, et al.
Publicado: (2008)

Generalized activity equations for spiking neural network dynamics
por: Buice, Michael A., et al.
Publicado: (2013)

Training Deep Spiking Neural Networks Using Backpropagation
por: Lee, Jun Haeng, et al.
Publicado: (2016)

Exploring the Connection Between Binary and Spiking Neural Networks
por: Lu, Sen, et al.
Publicado: (2020)

Neuroevolution Guided Hybrid Spiking Neural Network Training
por: Lu, Sen, et al.
Publicado: (2022)

Backpropagation With Sparsity Regularization for Spiking Neural Network Learning
por: Yan, Yulong, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_ggdvq905q07laocfnhhr1kg30a