Image from Syndetics
Neural networks : a comprehensive foundation / Simon Haykin.
Material type:
TextPublication details: Upper Saddle River, NJ : Prentice Hall, 1999.Edition: 2nd edISBN: - 0132733501
- 006.32 21
- QA76.87
Contents:
1. Introduction -- 2. Learning Processes -- 3. Single Layer Perceptrons -- 4. Multilayer Perceptrons -- 5. Radial-Basis Function Networks -- 6. Support Vector Machines -- 7. Committee Machines -- 8. Principal Components Analysis -- 9. Self-Organizing Maps -- 10. Information-Theoretic Models -- 11. Stochastic Machines And Their Approximates Rooted in Statistical Mechanics -- 12. Neurodynamic Programming -- 13. Temporal Processing Using Feedforward Networks -- 14. Neurodynamics -- 15. Dynamically Driven Recurrent Networks.
| Item type | Home library | Call number | Status | Date due | Barcode | Item holds | |
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Two Week Loan
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College Lane Learning Resources Centre Main Shelves | 006.3 HAY (Browse shelf(Opens below)) | Available | 4404422390 | |||
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Two Week Loan
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College Lane Learning Resources Centre Main Shelves | 006.3 HAY (Browse shelf(Opens below)) | Available | 4404422372 | |||
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College Lane Learning Resources Centre Main Shelves | 006.3 HAY (Browse shelf(Opens below)) | Available | 6000092911 | |||
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Two Week Loan
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College Lane Learning Resources Centre Main Shelves | 006.3 HAY (Browse shelf(Opens below)) | Available | 6000092900 |
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Enhanced descriptions from Syndetics:
1. Introduction -- 2. Learning Processes -- 3. Single Layer Perceptrons -- 4. Multilayer Perceptrons -- 5. Radial-Basis Function Networks -- 6. Support Vector Machines -- 7. Committee Machines -- 8. Principal Components Analysis -- 9. Self-Organizing Maps -- 10. Information-Theoretic Models -- 11. Stochastic Machines And Their Approximates Rooted in Statistical Mechanics -- 12. Neurodynamic Programming -- 13. Temporal Processing Using Feedforward Networks -- 14. Neurodynamics -- 15. Dynamically Driven Recurrent Networks.