Dynamics of spiking map-based neural networks in problems of supervised learning

DOI10.1016/j.cnsns.2020.105399zbMath1453.92018OpenAlexW3034495101MaRDI QIDQ2208202

Oleg V. Maslennikov, Vladimir I. Nekorkin, Mechislav M. Pugavko

Publication date: 23 October 2020

Published in: Communications in Nonlinear Science and Numerical Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cnsns.2020.105399

zbMATH Keywords

supervised learningrecurrent networkmap-based neuron

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Neural networks for/in biological studies, artificial life and related topics (92B20)

Cites Work

• Reservoir computing approaches to recurrent neural network training
• MAP BASED MODELS IN NEURODYNAMICS
• Chaotic oscillations in a map-based model of neural activity
• Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations
• Transient sequences in a hypernetwork generated by an adaptive network of spiking neurons
• Opening the Black Box: Low-Dimensional Dynamics in High-Dimensional Recurrent Neural Networks
• Unnamed Item
• Unnamed Item

This page was built for publication: Dynamics of spiking map-based neural networks in problems of supervised learning