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A Novel Single Neuron Perceptron with Universal Approximation and XOR Computation Properties
Joint Authors
Lotfi, Ehsan
Akbarzadeh-T, Mohammad-R
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-28
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
We propose a biologically motivated brain-inspired single neuron perceptron (SNP) with universal approximation and XOR computation properties.
This computational model extends the input pattern and is based on the excitatory and inhibitory learning rules inspired from neural connections in the human brain’s nervous system.
The resulting architecture of SNP can be trained by supervised excitatory and inhibitory online learning rules.
The main features of proposed single layer perceptron are universal approximation property and low computational complexity.
The method is tested on 6 UCI (University of California, Irvine) pattern recognition and classification datasets.
Various comparisons with multilayer perceptron (MLP) with gradient decent backpropagation (GDBP) learning algorithm indicate the superiority of the approach in terms of higher accuracy, lower time, and spatial complexity, as well as faster training.
Hence, we believe the proposed approach can be generally applicable to various problems such as in pattern recognition and classification.
American Psychological Association (APA)
Lotfi, Ehsan& Akbarzadeh-T, Mohammad-R. 2014. A Novel Single Neuron Perceptron with Universal Approximation and XOR Computation Properties. Computational Intelligence and Neuroscience،Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-495407
Modern Language Association (MLA)
Lotfi, Ehsan& Akbarzadeh-T, Mohammad-R. A Novel Single Neuron Perceptron with Universal Approximation and XOR Computation Properties. Computational Intelligence and Neuroscience No. 2014 (2014), pp.1-6.
https://search.emarefa.net/detail/BIM-495407
American Medical Association (AMA)
Lotfi, Ehsan& Akbarzadeh-T, Mohammad-R. A Novel Single Neuron Perceptron with Universal Approximation and XOR Computation Properties. Computational Intelligence and Neuroscience. 2014. Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-495407
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-495407