Neural networks for pattern recognition / Christopher M. Bishop
Tipo de material:
TextoDetalles de publicación: Oxford : Oxford University Press, 1995 2008 reimpEdición: 1st ed., 11th printingDescripción: XIV, 482 p. : gráf. ; 24 cmISBN: 0-19-853864-2Tema(s): Redes neuronales (Informática) | Inteligencia artificialResumen: This book provides the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition. After introducing the basic concepts of pattern recognition, the book describes techniques for modelling probability density functions, and discusses the properties and relative merits of the multi-layer perceptron and radial basis function network models. It also motivates the use of various forms of error functions, and reviews the principal algorithms for error function minimization. As well as providing a detailed discussion of learning and generalization in neural networks, the book also covers the important topics of data processing, feature extraction, and prior knowledge. The book concludes with an extensive treatment of Bayesian techniques and their applications to neural networks.Resumen: Índice: 1. Statistical pattern recognition; 2. Probability density estimation; 3. Single-layer networks; 4. The multi-layer perceptron; 5. Radial basis functions; 6. Error functions; 7. Parameter optimization algorithms; 8. Pre-processing and feature extraction; 9. Learning and generalization; 10. Bayesian techniques.
| Tipo de ítem | Biblioteca de origen | Signatura | URL | Estado | Fecha de vencimiento | Código de barras | Reserva de ítems | Bibliografía recomendada |
|---|---|---|---|---|---|---|---|---|
| Manuales | 03. BIBLIOTECA INGENIERÍA PUERTO REAL | 681.3/BIS/neu (Navegar estantería(Abre debajo)) | Texto completo | Disponible Ubicación en estantería | Bibliomaps® | 3742374329 |
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| Manuales | 03. BIBLIOTECA INGENIERÍA PUERTO REAL | 681.3/BIS/neu (Navegar estantería(Abre debajo)) | Texto completo | Disponible Ubicación en estantería | Bibliomaps® | 3742374445 | |||
| Manuales | 03. BIBLIOTECA INGENIERÍA PUERTO REAL | 681.3/BIS/neu (Navegar estantería(Abre debajo)) | Texto completo | Disponible Ubicación en estantería | Bibliomaps® | 3742374383 |
Índice
Bibliografía: p. [457]-475
This book provides the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition. After introducing the basic concepts of pattern recognition, the book describes techniques for modelling probability density functions, and discusses the properties and relative merits of the multi-layer perceptron and radial basis function network models. It also motivates the use of various forms of error functions, and reviews the principal algorithms for error function minimization. As well as providing a detailed discussion of learning and generalization in neural networks, the book also covers the important topics of data processing, feature extraction, and prior knowledge. The book concludes with an extensive treatment of Bayesian techniques and their applications to neural networks.
Índice: 1. Statistical pattern recognition; 2. Probability density estimation; 3. Single-layer networks; 4. The multi-layer perceptron; 5. Radial basis functions; 6. Error functions; 7. Parameter optimization algorithms; 8. Pre-processing and feature extraction; 9. Learning and generalization; 10. Bayesian techniques.
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