Generalized neural networks for spectral analysis: dynamics and Liapunov functions
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Publication:1877570
DOI10.1016/J.NEUNET.2003.05.001zbMath1121.68398OpenAlexW2094131148WikidataQ52000951 ScholiaQ52000951MaRDI QIDQ1877570
Pedro J. Zufiria, José Manuel Vegas
Publication date: 19 August 2004
Published in: Neural Networks (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.neunet.2003.05.001
Lyapunov functionsStabilityPrincipal component analysisNonlinear dynamicsHomogeneous functionsGlobal behaviorHebbian networks
Learning and adaptive systems in artificial intelligence (68T05) Dynamical systems in biology (37N25)
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Uses Software
Cites Work
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- A simplified neuron model as a principal component analyzer
- A neural network for computing eigenvectors and eigenvalues
- Ordinary differential equations. An introduction to nonlinear analysis. Transl. from the German by Gerhard Metzen
- A Theory for Learning by Weight Flow on Stiefel-Grassman Manifold
- Absolute stability of global pattern formation and parallel memory storage by competitive neural networks
- Unconstrained Variational Principles for Eigenvalues of Real Symmetric Matrices
- Analysis of recursive stochastic algorithms
- The Geometry of Algorithms with Orthogonality Constraints
- Differential Equations Defined by the Sum of two Quasi-Homogeneous Vector Fields
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