| ### Index
Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks
Russell D. Reed and Robert J. Marks II
Copyright © 1999 Massachusetts Institute of Technology

## Index

### H

Hard-limiters, 134
Hard weight sharing, 269
Hebbian learning, 30
Hessian matrix
approximation of, 129-132
gradient-based methods and, 163, 166-167, 170-174, 182
ill-conditioned, 127-128, 179
learning rate and, 72, 81-84
node splitting and, 214-215
problem size and, 157
properties of, 127-132
pruning and, 223-225
quadratic function and, 179
search then converge method and, 147
Hidden layers
definition of, 2, 31
equivalent solutions and, 194
error surface and, 119, 124, 126
representational capabilities and, 32-47
weight-space symmetries and, 119
Hidden nodes
approximation error and, 37
derivative calculation for, 54, 56
nonrandom initialization and, 106, 107, 108
random initialization and, 102, 103-104
Hint functions, 275
Holdout method, 257-258
Homogeneously linear separability, 20
Hooke-Jeeves pattern search, 160-161
Hopfield networks, 49, 183
Hyperplanes, 15-18
capacity of, 20-23
nonrandom initialization and, 107
random initialization and, 102, 103
representational capability and, 42-44
stair-steps and, 114

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