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00000cam a2200000 7i4500 |
| 001 |
0000094309 |
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20200616093000.0 |
| 008 |
180417s2009 nju eng |
| 020 |
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|a 0131293761
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| 020 |
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|a 9780131293762
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| 040 |
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|a UniSZA
|e rda
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| 050 |
0 |
0 |
|a QA76.87
|b .H39 2009
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| 090 |
0 |
0 |
|a QA76.87
|b .H39 2009
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| 100 |
1 |
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|a Haykin, Simon S. ,
|d 1931- ,
|e author
|
| 245 |
1 |
0 |
|a Neural networks and learning machines
|c Simon Haykin
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| 250 |
|
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|a Third edition
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| 264 |
|
1 |
|a Upper Saddle River, New Jersey :
|b Pearson
|c c2009
|
| 300 |
|
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|a 934 pages :
|b illustration ;
|c 24 cm.
|
| 336 |
|
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|a text
|2 rdacontent
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| 337 |
|
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|a unmediated
|2 rdamedia
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| 338 |
|
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|a volume
|2 rdacarrier
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| 504 |
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|a Includes bibliographical references (pages 875-915) and index
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| 505 |
1 |
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|a 1. Rosenblatt's perceptron -- 2. Model building through regression -- 3. The least-mean-square algorithm -- 4. Multilayer perceptrons -- 5. Kernel methods and radial-basis function networks -- 6. Support vector machines -- 7. Regularization theory -- 8. Principal-components analysis -- 9. Self-organizing maps -- 10. Information-theoretic learning models -- 11. Stochastic methods rooted in statistical mechanics -- 12. Dynamic programming -- 13. Neurodynamics -- 14. Bayesian filtering for state estimation of dynamic systems -- 15. Dynamically driven recurrent networks
|
| 650 |
|
0 |
|a Adaptive filters
|
| 650 |
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0 |
|a Neural networks (Computer science)
|
| 999 |
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|a 1000173700
|b Book
|c Open Shelf (1 Day)
|e Tembila Campus
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