 | 2009 |
|---|
| 12 |       | Ralph Linsker:
Neural learning of Kalman filtering, Kalman control, and system identification.
IJCNN 2009: 1835-1842 |
| 2008 |
|---|
| 11 | | Ralph Linsker:
Neural network learning of optimal Kalman prediction and control
CoRR abs/0805.4247: (2008) |
| 10 | | Ralph Linsker:
Neural network learning of optimal Kalman prediction and control.
Neural Networks 21(9): 1328-1343 (2008) |
| 2005 |
|---|
| 9 | | Ralph Linsker:
Improved local learning rule for information maximization and related applications.
Neural Networks 18(3): 261-265 (2005) |
| 2004 |
|---|
| 8 | | Alina Beygelzimer,
Geoffrey Grinstein,
Ralph Linsker,
Irina Rish:
Improving Network Robustness.
ICAC 2004: 322-323 |
| 1997 |
|---|
| 7 | | Ralph Linsker:
A Local Learning Rule That Enables Information Maximization for Arbitrary Input Distributions.
Neural Computation 9(8): 1661-1665 (1997) |
| 1992 |
|---|
| 6 | | Ralph Linsker:
Deriving Receptive Fields Using an Optimal Encoding Criterion.
NIPS 1992: 953-960 |
| 5 | | Ralph Linsker:
Local Synaptic Learning Rules Suffice to Maximize Mutual Information in a Linear Network.
Neural Computation 4(5): 691-702 (1992) |
| 1988 |
|---|
| 4 | | Ralph Linsker:
An Application of the Principle of Maximum Information Preservation to Linear Systems.
NIPS 1988: 186-194 |
| 3 | | Ralph Linsker:
Self-Organization in a Perceptual Network.
IEEE Computer 21(3): 105-117 (1988) |
| 1987 |
|---|
| 2 | | Ralph Linsker:
Towards an Organizing Principle for a Layered Perceptual Network.
NIPS 1987: 485-494 |
| 1984 |
|---|
| 1 |  | Ralph Linsker:
An Iterative-Improvement Penalty-Function-Driven Wire Routing System.
IBM Journal of Research and Development 28(5): 613-624 (1984) |
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