Abstract
A quick tour of relevant algebra is York and Yi, Clifford neural networks and chaotic time series. http://www.deepstem.com/Bio/SysSci-CNN-york.pdf, 2013, [1].
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Notes
- 1.
Hitzer, E., Introduction to Clifford’s Geometric Algebra, SICE Journal of Control, Measurement, and System Integration, 2011, 4(1), 1–10.
- 2.
Buchholz, S., and Tachibana, K., and Hitzer, E. M.S., Optimal Learning Rates for Clifford Neurons, Lecture Notes in Computer Science, 2007, 4668, 864–873.
- 3.
Ding, L., and Feng, H., and Hua, L., Multi-degree of Freedom Neurons Geometric Computation Based on Clifford Algebra, Fourth International Conference on Intelligent Computation Technology and Automation, 2011, 177–180.
- 4.
Buchholz, S., A Theory of Neural Computation with Clifford Algebras, Kiel, 2005, http://www.informatik.uni-kiel.de/inf/Sommer/doc/Dissertationen/Sven_Buchholz/diss.pdf.
- 5.
Ahn, S. H, 2009. Math. http://www.songho.ca/math/index.html.
- 6.
Ahn, S. H, 2009. Math. http://www.songho.ca/math/index.html.
References
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Iatan, I.F. (2017). A Fuzzy Gaussian Clifford Neural Network. In: Issues in the Use of Neural Networks in Information Retrieval. Studies in Computational Intelligence, vol 661. Springer, Cham. https://doi.org/10.1007/978-3-319-43871-9_5
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