Document Detail


Riemannian-Gradient-Based Learning on the Complex Matrix-Hypersphere.
MedLine Citation:
PMID:  21984497     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
This brief tackles the problem of learning over the complex-valued matrix-hypersphere Sɑn, p(C). The developed learning theory is formulated in terms of Riemannian-gradient-based optimization of a regular criterion function and is implemented by a geodesic-stepping method. The stepping method is equipped with a geodesic-search sub-algorithm to compute the optimal learning stepsize at any step. Numerical results show the effectiveness of the developed learning method and of its implementation.
Authors:
Simone Fiori
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-10-06
Journal Detail:
Title:  IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council     Volume:  -     ISSN:  1941-0093     ISO Abbreviation:  -     Publication Date:  2011 Oct 
Date Detail:
Created Date:  2011-10-10     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101211035     Medline TA:  IEEE Trans Neural Netw     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
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