Statistical Approach to Neural Networks for Pattern Recognition
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Statistical Approach to Neural Networks for Pattern Recognition
Dunne, Robert A.
John Wiley & Sons Inc
08/2007
288
Dura
Inglês
9780471741084
15 a 20 dias
588
Descrição não disponível.
Notation and Code Examples. Preface.
Acknowledgments.
1. Introduction.
2. The Multi-Layer Perception Model.
3. Linear Discriminant Analysis.
4. Activation and Penalty Functions.
5. Model Fitting and Evaluation.
6. The Task-Based MLP.
7. Incorporating Spatial Information into an MLP Classifier.
8. Influence Curves for the Multi-Layer Perceptron Classifier.
9. The Sensitivity Curves of the MLP Classifier.
10. A Robust Fitting Procedure for MLP Models.
11. Smoothed Weights.
12. Translation Invariance.
13. Fixed-slope Training.
Appendix A. Function Minimization.
Appendix B. Maximum Values of the Influence Curve.
Topic Index.
Acknowledgments.
1. Introduction.
2. The Multi-Layer Perception Model.
3. Linear Discriminant Analysis.
4. Activation and Penalty Functions.
5. Model Fitting and Evaluation.
6. The Task-Based MLP.
7. Incorporating Spatial Information into an MLP Classifier.
8. Influence Curves for the Multi-Layer Perceptron Classifier.
9. The Sensitivity Curves of the MLP Classifier.
10. A Robust Fitting Procedure for MLP Models.
11. Smoothed Weights.
12. Translation Invariance.
13. Fixed-slope Training.
Appendix A. Function Minimization.
Appendix B. Maximum Values of the Influence Curve.
Topic Index.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
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Notation and Code Examples. Preface.
Acknowledgments.
1. Introduction.
2. The Multi-Layer Perception Model.
3. Linear Discriminant Analysis.
4. Activation and Penalty Functions.
5. Model Fitting and Evaluation.
6. The Task-Based MLP.
7. Incorporating Spatial Information into an MLP Classifier.
8. Influence Curves for the Multi-Layer Perceptron Classifier.
9. The Sensitivity Curves of the MLP Classifier.
10. A Robust Fitting Procedure for MLP Models.
11. Smoothed Weights.
12. Translation Invariance.
13. Fixed-slope Training.
Appendix A. Function Minimization.
Appendix B. Maximum Values of the Influence Curve.
Topic Index.
Acknowledgments.
1. Introduction.
2. The Multi-Layer Perception Model.
3. Linear Discriminant Analysis.
4. Activation and Penalty Functions.
5. Model Fitting and Evaluation.
6. The Task-Based MLP.
7. Incorporating Spatial Information into an MLP Classifier.
8. Influence Curves for the Multi-Layer Perceptron Classifier.
9. The Sensitivity Curves of the MLP Classifier.
10. A Robust Fitting Procedure for MLP Models.
11. Smoothed Weights.
12. Translation Invariance.
13. Fixed-slope Training.
Appendix A. Function Minimization.
Appendix B. Maximum Values of the Influence Curve.
Topic Index.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
