Single dendritic neuron model trained by spherical search algorithm for classification

Jia Yu, Jiarui Shi, Zhen Li, Houtian He, Shangce Gao*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

Recently, the single dendritic neuron with non-linear locality has been focused by many neuroscience researches. The dendrites are composed of several branches, and these branches correspond to three distributions in coordinate, which are used to classify the training data as required. To develop a new dendritic neuron model (DNM) for solving more practical problems, we use a recently proposed state-of-the-art optimization algorithm called spherical search algorithm as the training algorithm. The results based on several real-world classification tasks suggest that the proposed learning algorithm is more effective and promising for training DNM in comparison with another recently proposed differential evolution learning algorithm. It thereafter indicates that DNM, as a single neuron model, is a suitable and powerful classifier.

Original languageEnglish
Title of host publicationProceedings of 2020 IEEE International Conference on Progress in Informatics and Computing, PIC 2020
EditorsYinglin Wang, Yanghua Xiao
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages30-33
Number of pages4
ISBN (Electronic)9781728170862
DOIs
StatePublished - 2020/12/18
Event7th IEEE International Conference on Progress in Informatics and Computing, PIC 2020 - Shanghai, China
Duration: 2020/12/182020/12/20

Publication series

NameProceedings of 2020 IEEE International Conference on Progress in Informatics and Computing, PIC 2020

Conference

Conference7th IEEE International Conference on Progress in Informatics and Computing, PIC 2020
Country/TerritoryChina
CityShanghai
Period2020/12/182020/12/20

Keywords

  • Artificial neural network
  • Computational intelligence
  • Deep learning
  • Dendritic neuron model
  • Learning algorithm
  • Spherical search algorithm

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Signal Processing
  • Control and Optimization

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