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Highly Parallel Computation
Highly Parallel Computation
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Highly Parallel Computation

Denning, Peter J. ; Tichy, Walter F.

Science (American Association for the Advancement of Science), 1990-11, Vol.250 (4985), p.1217-1222 [Periódico revisado por pares]

Legacy CDMS: American Society for the Advancement of Science

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2
Ultracomputers: A Teraflop Before Its Time
Ultracomputers: A Teraflop Before Its Time
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Ultracomputers: A Teraflop Before Its Time

Bell, Gordon

Science (American Association for the Advancement of Science), 1992-04, Vol.256 (5053), p.64-64 [Periódico revisado por pares]

WASHINGTON: American Society for the Advancement of Science

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3
Microprocessors: From Desktops to Supercomputers
Microprocessors: From Desktops to Supercomputers
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Microprocessors: From Desktops to Supercomputers

Baskett, Forest ; Hennessy, John L.

Science (American Association for the Advancement of Science), 1993-08, Vol.261 (5123), p.864-871 [Periódico revisado por pares]

Washington, DC: American Society for the Advancement of Science

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4
A Defect-Tolerant Computer Architecture: Opportunities for Nanotechnology
A Defect-Tolerant Computer Architecture: Opportunities for Nanotechnology
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A Defect-Tolerant Computer Architecture: Opportunities for Nanotechnology

Heath, James R. ; Kuekes, Philip J. ; Snider, Gregory S. ; Williams, R. Stanley

Science (American Association for the Advancement of Science), 1998-06, Vol.280 (5370), p.1716-1721 [Periódico revisado por pares]

Washington, DC: American Society for the Advancement of Science

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5
Selecting radial basis function network centers with recursive orthogonal least squares training
Selecting radial basis function network centers with recursive orthogonal least squares training
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Selecting radial basis function network centers with recursive orthogonal least squares training

Gomm, J.B. ; Yu, D.L.

IEEE transactions on neural networks, 2000, Vol.11 (2), p.306-314

United States: IEEE

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6
A local linearized least squares algorithm for training feedforward neural networks
A local linearized least squares algorithm for training feedforward neural networks
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A local linearized least squares algorithm for training feedforward neural networks

Stan, O. ; Kamen, E.

IEEE transactions on neural networks, 2000, Vol.11 (2), p.487-495

United States: IEEE

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7
Existence and learning of oscillations in recurrent neural networks
Existence and learning of oscillations in recurrent neural networks
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Existence and learning of oscillations in recurrent neural networks

Townley, S. ; Ilchmann, A. ; Weiss, M.G. ; Mcclements, W. ; Ruiz, A.C. ; Owens, D.H. ; Pratzel-Wolters, D.

IEEE transactions on neural networks, 2000-01, Vol.11 (1), p.205-214

United States: IEEE

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8
A new supervised learning algorithm for multilayered and interconnected neural networks
A new supervised learning algorithm for multilayered and interconnected neural networks
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A new supervised learning algorithm for multilayered and interconnected neural networks

Yamamoto, Y. ; Nikiforuk, P.N.

IEEE transactions on neural networks, 2000-01, Vol.11 (1), p.36-46

United States: IEEE

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9
Design of neural networks for fast convergence and accuracy: dynamics and control
Design of neural networks for fast convergence and accuracy: dynamics and control
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Design of neural networks for fast convergence and accuracy: dynamics and control

Maghami, P.G. ; Sparks, D.W.

IEEE transactions on neural networks, 2000-01, Vol.11 (1), p.113-123

United States: IEEE

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10
Robust recursive least squares learning algorithm for principal component analysis
Robust recursive least squares learning algorithm for principal component analysis
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Robust recursive least squares learning algorithm for principal component analysis

Shan, O ; Bao, Z ; Liao, G S

IEEE transactions on neural networks, 2000-01, Vol.11 (1), p.215-221

United States: IEEE

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