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A Dendritic Neuron Model with Adaptive Synapses Trained by Differential Evolution Algorithm
Joint Authors
Gao, Shangce
Todo, Yuki
Wang, Zhe
Wang, Jiaxin
Yang, Haichuan
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-01-17
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Abstract EN
A dendritic neuron model with adaptive synapses (DMASs) based on differential evolution (DE) algorithm training is proposed.
According to the signal transmission order, a DNM can be divided into four parts: the synaptic layer, dendritic layer, membrane layer, and somatic cell layer.
It can be converted to a logic circuit that is easily implemented on hardware by removing useless synapses and dendrites after training.
This logic circuit can be designed to solve complex nonlinear problems using only four basic logical devices: comparators, AND (conjunction), OR (disjunction), and NOT (negation).
To obtain a faster and better solution, we adopt the most popular DE for DMAS training.
We have chosen five classification datasets from the UCI Machine Learning Repository for an experiment.
We analyze and discuss the experimental results in terms of the correct rate, convergence rate, ROC curve, and the cross-validation and then compare the results with a dendritic neuron model trained by the backpropagation algorithm (BP-DNM) and a neural network trained by the backpropagation algorithm (BPNN).
The analysis results show that the DE-DMAS shows better performance in all aspects.
American Psychological Association (APA)
Wang, Zhe& Gao, Shangce& Wang, Jiaxin& Yang, Haichuan& Todo, Yuki. 2020. A Dendritic Neuron Model with Adaptive Synapses Trained by Differential Evolution Algorithm. Computational Intelligence and Neuroscience،Vol. 2020, no. 2020, pp.1-19.
https://search.emarefa.net/detail/BIM-1138726
Modern Language Association (MLA)
Wang, Zhe…[et al.]. A Dendritic Neuron Model with Adaptive Synapses Trained by Differential Evolution Algorithm. Computational Intelligence and Neuroscience No. 2020 (2020), pp.1-19.
https://search.emarefa.net/detail/BIM-1138726
American Medical Association (AMA)
Wang, Zhe& Gao, Shangce& Wang, Jiaxin& Yang, Haichuan& Todo, Yuki. A Dendritic Neuron Model with Adaptive Synapses Trained by Differential Evolution Algorithm. Computational Intelligence and Neuroscience. 2020. Vol. 2020, no. 2020, pp.1-19.
https://search.emarefa.net/detail/BIM-1138726
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1138726