Complex-Valued Neurocomputing and Singular Points

Author	Tohru Nitta	en
Issued Date	2015-10-01	en
Abstract	Context: Recently, the singular points of neural networks have attracted attention from the artificial intelligence community, and their interesting properties have been demonstrated. The objective of this study is to provide an overview of studies on the singularities of complex-valued neural networks. Evidence Acquisition: This review is based on the relevant literature on complex-valued neural networks and singular points. Results: Review of the studies and available literature on the subject area shows that the singular points of complex-valued neural networks have negative effects on learning, as do those of real-valued neural networks. However, the nature of the singular points in complex-valued neural networks is superior in quality, and the methods for improving the learning performance have been proposed. Conclusions: A complex-valued neural network could be a promising learning method from the viewpoint of a singularity.	en
DOI	https://doi.org/10.5812/archneurosci.27461	en
Keyword	Neural Network	en
Keyword	Learning	en
Keyword	Non-linear Dynamics	en
Publisher	Brieflands	en
Title	Complex-Valued Neurocomputing and Singular Points	en
Type	Review Article	en

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