Page 10 -

6.3.1 String Grammars ......................................................... 250
6.3.2 Picture Description Language ..................................... 253
6.3.3 Grammar Types .......................................................... 255
6.3.4 Finite-State Automata .................................................. 257
6.3.5 Attributed Grammars ................................................... 260
6.3.6 Stochastic Grammars .................................................. 261
6.3.7 Grammatical Inference ................................................ 264
6.4 Structural Matching .................................................................. 265
6.4.1 String Matching ........................................................... 265
6.4.2 Probabilistic Relaxation Matching ............................... 271
6.4.3 Discrete Relaxation Matching ...................................... 274
6.4.4 Relaxation Using Hopfield Networks ........................... 275
6.4.5 Graph and Tree Matching ........................................... 279
Bibliography .......................................................................................... 283
Exercises .............................................................................................. 285

Appendix A . CD Datasets .................................................................. 291

Breast Tissue ............................................................................ 291
Clusters .................................................................................... 292
Cork Stoppers ........................................................................... 292
Crimes ...................................................................................... 293
Cardiotocographic Data ............................................................ 293
Electrocardiograms .................................................................. 294
Foetal Heart Rate Signals ........................................................ 295
FHR-Apgar ............................................................................... 295
Firms ......................................................................................... 296
Foetal Weight ........................................................................... 296
Food ......................................................................................... 297
Fruits ......................................................................................... 297
Impulses on Noise .................................................................... 297
MLP Sets .................................................................................. 298
Norm2c2d ................................................................................. 298
Rocks ........................................................................................ 299
Stock Exchange ....................................................................... 299
Tanks ........................................................................................ 300
Weather .................................................................................... 300

Appendix B . CD Tools ........................................................................ 301

B.l Adaptive Filtering ...................................................................... 301
B.2 Density Estimation .................................................................... 301
B.3 Design Set Size ........................................................................ 302