| ### 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

### R

Radial basis functions, 198, 288
Radial features, 114-116
Random initialization, 97-98
calculations for, 98-102
constrained, 103-105
error surface and, 120, 121, 133
parameters for, 100-102
Randomness
learning rate and, 80
on-line learning and, 60, 80
search then converge method and, 147
Random restarts, 121-123, 157
Regions, and hyperplanes, 42-44
Regression, 23, 29, 293-298
classification versus, 156-157
projection pursuit, 217
Regularization, 266-267, 281-283
Reinforcement learning, 12
Replicated networks, 272-273
Representational capabilities, 31-47
Robustness, 157
Root mean square (RMS) error function, 77, 222,285
Rosenblatt's perception, 28-29
Rprop (resilient propagation), 85, 142-145, 152, 252, 291
Rule-based systems, 109-110, 217, 275-276

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