Sensitivity Analysis for Neural Networks by Daniel S Yeung
Artificial neural networks are used to model systems that receive inputs and produce outputs. It covers sensitivity analysis of multilayer perceptron neural networks and radial basis function neural networks, two widely used models in the machine learning field.-
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Massively Parallel Evolutionary Computation on GPGPUs
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From the reviews:
“Neural Networks are seen as an information paradigm inspired by the way the human brain processes information… The book may be used by researchers in diverse domains, such as neural networks, machine learning, computer engineering, etc., facing problems connected to sensitivity analysis of neural networks.” (Florin Gorunescu, Zentralblatt MATH, Vol. 1189, 2010)| SKU | Unavailable |
| ISBN 13 | 9783642025310 |
| ISBN 10 | 3642025315 |
| Title | Sensitivity Analysis for Neural Networks |
| Author | Daniel S Yeung |
| Series | Natural Computing Series |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Springer |
| Year published | 2009-11-18 |
| Number of pages | 86 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |