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Open access
Springer Nature
Lecture Notes in Computer Science
,  pages 864-873

Optimal Learning Rates for Clifford Neurons

Publication type: Book Chapter
Publication date: 2007-09-13
Springer Nature
scimago Q2
SJR: 0.352
CiteScore: 2.4
Impact factor: —
ISSN: 03029743, 16113349, 18612075, 18612083
Abstract
Neural computation in Clifford algebras, which include familiar complex numbers and quaternions as special cases, has recently become an active research field. As always, neurons are the atoms of computation. The paper provides a general notion for the Hessian matrix of Clifford neurons of an arbitrary algebra. This new result on the dynamics of Clifford neurons then allows the computation of optimal learning rates. A thorough discussion of error surfaces together with simulation results for different neurons is also provided. The presented contents should give rise to very efficient second–order training methods for Clifford Multi-layer perceptrons in the future.
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GOST Copy
BUCHHOLZ S., Tachibana K., Hitzer E. M. S. Optimal Learning Rates for Clifford Neurons // Lecture Notes in Computer Science. 2007. pp. 864-873.
GOST all authors (up to 50) Copy
BUCHHOLZ S., Tachibana K., Hitzer E. M. S. Optimal Learning Rates for Clifford Neurons // Lecture Notes in Computer Science. 2007. pp. 864-873.
RIS |
Cite this
RIS Copy
TY - GENERIC
DO - 10.1007/978-3-540-74690-4_88
UR - https://doi.org/10.1007/978-3-540-74690-4_88
TI - Optimal Learning Rates for Clifford Neurons
T2 - Lecture Notes in Computer Science
AU - BUCHHOLZ, SVEN
AU - Tachibana, Kanta
AU - Hitzer, Eckhard M S
PY - 2007
DA - 2007/09/13
PB - Springer Nature
SP - 864-873
SN - 0302-9743
SN - 1611-3349
SN - 1861-2075
SN - 1861-2083
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@incollection{2007_BUCHHOLZ,
author = {SVEN BUCHHOLZ and Kanta Tachibana and Eckhard M S Hitzer},
title = {Optimal Learning Rates for Clifford Neurons},
publisher = {Springer Nature},
year = {2007},
pages = {864--873},
month = {sep}
}