Contents......Page 7
1
Introduction......Page 18
Part I
Single Stream Networks......Page 23
2.1 Hebbian Learning......Page 26
2.2 Quantification of Information......Page 28
2.6 Anti-Hebbian Learning......Page 38
2.7 Independent Component Analysis......Page 40
3 The Negative Feedback Network......Page 45
4 Peer-Inhibitory Neurons......Page 71
5
Multiple Cause Data......Page 99
6 Exploratory Data Analysis......Page 124
7 Topology Preserving Maps......Page 150
8 Maximum Likelihood Hebbian Learning......Page 182
Part II
Dual Stream Networks......Page 200
9 Two Neural Networks for Canonical Correlation Analysis......Page 203
10 Alternative Derivations of CCA Networks......Page 221
11 Kernel and Nonlinear Correlations......Page 229
12 Exploratory Correlation Analysis......Page 259
13 Multicollinearity and Partial Least Squares......Page 286
14 Twinned Principal Curves......Page 301
15 The Future......Page 318
A Negative Feedback Artificial Neural Networks......Page 323
B Previous Factor Analysis Models......Page 330
C Related Models for ICA......Page 348
D Previous Dual Stream Approaches......Page 360
E
Data Sets......Page 370
References......Page 377
Index......Page 386
