Pattern Recognition and Neural Networks

1. Introduction and examples; 2. Statistical decision theory; 3. Linear discriminant analysis; 4. Flexible discriminants; 5. Feed-forward neural networks; 6. Non-parametric methods; 7. Tree-structured classifiers; 8. Belief networks; 9. Unsupervised methods; 10. Finding good pattern features; Appendix: statistical sidelines; Glossary; References; Author index; Subject index.

Brian D. Ripley 

Mathematik Wahrscheinlichkeitstheorie Neural Networks Computers - General Information Optical Data Processing Mathematik/Wahrscheinlichkeitstheorie 

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