Geometric Algebra Based Neural Networks

  • Mirek Kárný
  • Kevin Warwick
  • Vera Kůrková
Part of the Perspectives in Neural Computing book series (PERSPECT.NEURAL)


In the last period there were introduced some new types of neural networks based on a more general type of algebra. They obey the multidimensional neural activities compared to the one-dimensional neural activity within the standard neural network framework. Instead of using basically the product of two scalar values they utilise some special algebraic product of two multidimensional quantities. Most of them can be considered as a special type of geometric (Clifford) algebra [1], [2] based neural networks (GANNs).


Output Neuron Geometric Algebra Input Element Geometric Product Geometric Multiplication 
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Copyright information

© Springer-Verlag London Limited 1998

Authors and Affiliations

  • Mirek Kárný
    • 1
  • Kevin Warwick
    • 2
  • Vera Kůrková
    • 3
  1. 1.Institute of Information Theory & AutomationPrague 8Czech Republic
  2. 2.Department of CyberneticsUniversity of ReadingWhiteknights, ReadingUK
  3. 3.Institute of Computer ScienceAcademy of Sciences of the Czech RepublicPrague 8Czech Republic

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