A chaotic spiking backpropagation approach to brain learning

Guanrong Chen

doi:10.1093/nsr/nwae070

A chaotic spiking backpropagation approach to brain learning

National Science Review 11(6)

Article 2024 English

Abstract

1 min read

A highlight of the chaotic spiking backpropagation (CSBP) method, which is a powerful tool for directly training spiking neural networks and helps to understand the learning mechanisms of human brain.

Discussion(0)

No comments yet. Be the first to comment.

Related publications

Article2016

A Circuit-Based Neural Network with Hybrid Learning of Backpropagation and Random Weight Change Algorithms

Changju Yang, Hyongsuk Kim, Shyam Prasad Adhikari, Leon O Chua

Article2025

A Neuromorphic Approach for Brain-Machine Interface Using Spiking Neural Networks

Guanting Liu, Ying Yan, Sizhen He, Jun Cai, Adrian David Cheok, Edmond Q. Wu, Aiguo Song

Article2017

Spiking neural network applications

Gaffari Çelik, Muhammed Fatih Talu

2017 International Artificial Intelligence and Data Processing Symposium (IDAP)

Article1995

<title>Fuzzy neural network with fast backpropagation learning</title>

Zhong Lin Wang, M. De Sario, Andrea Guerriero, R. Mugnuolo

Article2023

Deep Learning for Brain MRI Segmentation

Udita Sharma, Neeraj Kumar, Shafalii Sharma

A chaotic spiking backpropagation approach to brain learning

Abstract

Discussion(0)

Related publications

A Circuit-Based Neural Network with Hybrid Learning of Backpropagation and Random Weight Change Algorithms

A Neuromorphic Approach for Brain-Machine Interface Using Spiking Neural Networks

Spiking neural network applications

&lt;title&gt;Fuzzy neural network with fast backpropagation learning&lt;/title&gt;

Deep Learning for Brain MRI Segmentation

<title>Fuzzy neural network with fast backpropagation learning</title>