| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
A cascade associative memory model with a hierarchical memory structure
|
Hirahara, Makoto
|
|
2000
|
13 |
1 |
p. 41-50
10 p.
|
artikel
|
| 2 |
A learning rule for dynamic recruitment and decorrelation
|
Körding, K.P
|
|
2000
|
13 |
1 |
p. 1-9
9 p.
|
artikel
|
| 3 |
Anxiety-like behavior in rats: a computational model
|
Salum, C.
|
|
2000
|
13 |
1 |
p. 21-29
9 p.
|
artikel
|
| 4 |
A proposed name for aperiodic brain activity: stochastic chaos
|
Freeman, W.J
|
|
2000
|
13 |
1 |
p. 11-13
3 p.
|
artikel
|
| 5 |
Cascade associative memory storing hierarchically correlated patterns with various correlations
|
Hirahara, M
|
|
2000
|
13 |
1 |
p. 51-61
11 p.
|
artikel
|
| 6 |
How good are support vector machines?
|
Raudys, Š
|
|
2000
|
13 |
1 |
p. 17-19
3 p.
|
artikel
|
| 7 |
Neural net based MRAC for a class of nonlinear plants
|
Ahmed, M.S.
|
|
2000
|
13 |
1 |
p. 111-124
14 p.
|
artikel
|
| 8 |
Neural networks are useful tools for drug design
|
Schneider, G
|
|
2000
|
13 |
1 |
p. 15-16
2 p.
|
artikel
|
| 9 |
On impulsive autoassociative neural networks
|
Guan, Zhi-Hong
|
|
2000
|
13 |
1 |
p. 63-69
7 p.
|
artikel
|
| 10 |
Our Millennium Issue!
|
Grossberg, Stephen
|
|
2000
|
13 |
1 |
p. xi-
1 p.
|
artikel
|
| 11 |
Partially pre-calculated weights for the backpropagation learning regime and high accuracy function mapping using continuous input RAM-based sigma–pi nets
|
Neville, R.S.
|
|
2000
|
13 |
1 |
p. 91-110
20 p.
|
artikel
|
| 12 |
Pattern segmentation in a binary/analog world: unsupervised learning versus memory storing
|
Lourenço, C
|
|
2000
|
13 |
1 |
p. 71-89
19 p.
|
artikel
|
| 13 |
Reinforcement Learning: An Introduction; R.S. Sutton, A.G. Barto (Eds.); MIT Press, Cambridge, MA, 1998, 380 pages, ISBN 0-262-19398-1, $42.00
|
Rao, R.P.N
|
|
2000
|
13 |
1 |
p. 133-135
3 p.
|
artikel
|
| 14 |
Self-organization of orientation maps in a formal neuron model using a cluster learning rule
|
Kuroiwa, J.
|
|
2000
|
13 |
1 |
p. 31-40
10 p.
|
artikel
|
| 15 |
Training neural networks to be insensitive to weight random variations
|
Conti, M.
|
|
2000
|
13 |
1 |
p. 125-132
8 p.
|
artikel
|
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