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On Very Large Scale Hamiltonian Neural Nets

  • Wieslaw Sienko
  • Wieslaw Citko
Part of the Advances in Soft Computing book series (AINSC, volume 19)

Abstract

This paper presents how to design very large scale lossless neural nets (LONN), which can be used as Walsh-spectrum analyzer. This analysis relies on the orthogonality of weight matrix W where W is Hurwitz-Radon matrix. The unique feature of the LONN is the possibility to treat them either as algorithms or as Hamiltonian physical objects (Walsh Transformation Processors).

Keywords

Hamiltonian System Weight Matrix Hamiltonian Function Walsh Spectrum Compatible Connection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Wieslaw Sienko
    • 1
  • Wieslaw Citko
    • 1
  1. 1.Department of Electrical EngineeringGdynia Maritime AcademyGdyniaPoland

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