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- 17.1 Mono-Layered Associative Network.
- 17.1.1 Perceptron
- 17.1.2 Linear Separation
- 17.1.3 Limitations
- 17.1.4 Widrow-Ho® Rule
- 17.2 Back-Propagation Learning Algorithm.
- 17.2.1 Example: Prediction of 13C-NMR Shifts for Methyl Substituted Cyclohexanes
- 17.3 Radial Basis Function Networks
- 17.3.1 Theory
- 17.3.2 Training Algorithms
- 17.3.3 Algorithms for the Radial Basis Functions Selection
- 17.3.4 Design of Training Data Set for the Calibration
- Problem
- 17.3.5 Example of Applications
- Problems