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Neural networks for computing eigenvalues and eigenvectors
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Practical Methods of Optimization
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A neural network for computing eigenvectors and eigenvalues
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On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix
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Systolic designs for eigenvalue-eigenvector computations using matrix powers
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Practical methods of optimization
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Matrix computations and equation solving using structured networks and training
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An introduction to computing with neural nets
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Simple 'neural' optimization networks: An A/D converter, signal decision circuit, and a linear programming circuit
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Unconstrained Variational Principles for Eigenvalues of Real Symmetric Matrices
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The Symmetric Eigenvalue Problem
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