000K  utf8
1100  $c2005
1500  eng
2050  urn:nbn:de:gbv:8:1-zs-00000142-a8
3000  Buchholz, Sven
4000  A Theory of Neural Computation with Clifford Algebras$hChristian-Albrechts-Universität zu Kiel  [Buchholz, Sven]
4030  Kiel$nChristian-Albrechts-Universität zu Kiel
4209  The present thesis introduces Clifford Algebra as a framework for neural computation. Clifford Algebra subsumes the reals, complex numbers and quaternions. Neural computation with Clifford algebras is model--based. This principle is established by constructing Clifford algebras from quadratic spaces. Then the subspace grading inherent to any Clifford algebra is introduced, which allows the representation of different geometric entities like points, lines, and so on. The above features of Clifford algebras are then taken as motivation for introducing the Basic Clifford Neuron (BCN), which is solely based on the geometric product of the underlying Clifford algebra. Using BCNs the Linear Associator is generalized to the Clifford associator. As a second type of Clifford neuron the Spinor Clifford Neuron (SCN) is presented. The propagation function of a SCN is an orthogonal transformation. Examples of how Clifford neurons can be used advantageously are given, including the linear computation of Möbius transformations by a SCN. A systematic basis for Clifford neural computation is provided by the important notions of isomorphic Clifford neurons and isomorphic representations. After the neuron level is established, the discussion continues with (Spinor) Clifford Multilayer Perceptrons. The treatment is divided into two parts according to the type of activation function used. First, (Spinor) Clifford Multilayer Perceptrons with real-valued activation functions ((S)CMLPs) are studied. A generic Backpropagation algorithm for CMLPs is derived. Also, universal approximation theorems for (S)CMLPs are presented. The efficency of (S)CMLPs is shown in a couple of simulations. Finally, the class of Clifford Multilayer Perceptrons with Clifford-valued activation functions is studied.
4950  https://nbn-resolving.org/urn:nbn:de:gbv:8:1-zs-00000142-a8$xR$3Volltext$534
4961  https://macau.uni-kiel.de/receive/macau_mods_00001896
5051  004
5550  Clifford Algebra
5550  Clifford-Algebra
5550  Geometric Algebra
5550  Neural Computation
5550  Neural Networks
5550  Neuronales Netz