Supervised Learning with Complex-valued Neural Networks
Recent advancements in the field of telecommunications, medical imaging and signal processing deal with signals that are inherently time varying, nonlinear and complex-valued. The time varying, nonlinear characteristics of these signals can be effectively analyzed using artificial neural networks. ...
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| Autori principali: | , , |
|---|---|
| Natura: | Livre numérique |
| Lingua: | Anglais |
| Pubblicazione: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edizione: | 1st ed. 2013. |
| Serie: | Studies in Computational Intelligence
421 |
| Accesso online: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Supervised Learning with Complex-valued Neural Networks, Texte imprimé, 9783642294907 |
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| 041 | 0 | |a eng | |
| 082 | |a 006.3 | ||
| 100 | 1 | |a Suresh, Sundaram, |c informaticien. | |
| 245 | 1 | 0 | |a Supervised Learning with Complex-valued Neural Networks |c by Sundaram Suresh, Narasimhan Sundararajan, c. |
| 250 | |a 1st ed. 2013. | ||
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Studies in Computational Intelligence |v 421 |x 1860-9503 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a Introduction Fully Complex-valued Multi Layer Perceptron Networks Fully Complex-valued Radial Basis Function Networks Performance Study on Complex-valued Function Approximation Problems Circular Complex-valued Extreme Learning Machine Classifier Performance Study on Real-valued Classification Problems Complex-valued Self-regulatory Resource Allocation Network Conclusions and Scope for FutureWorks (CSRAN) | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a Recent advancements in the field of telecommunications, medical imaging and signal processing deal with signals that are inherently time varying, nonlinear and complex-valued. The time varying, nonlinear characteristics of these signals can be effectively analyzed using artificial neural networks. Furthermore, to efficiently preserve the physical characteristics of these complex-valued signals, it is important to develop complex-valued neural networks and derive their learning algorithms to represent these signals at every step of the learning process. This monograph comprises a collection of new supervised learning algorithms along with novel architectures for complex-valued neural networks. The concepts of meta-cognition equipped with a self-regulated learning have been known to be the best human learning strategy. In this monograph, the principles of meta-cognition have been introduced for complex-valued neural networks in both the batch and sequential learning modes. For applications where the computation time of the training process is critical, a fast learning complex-valued neural network called as a fully complex-valued relaxation network along with its learning algorithm has been presented. The presence of orthogonal decision boundaries helps complex-valued neural networks to outperform real-valued networks in performing classification tasks. This aspect has been highlighted. The performances of various complex-valued neural networks are evaluated on a set of benchmark and real-world function approximation and real-valued classification problems | ||
| 700 | 1 | |a Sundararajan, Narasimhan. |4 aut | |
| 700 | 1 | |a Savitha, Ramasamy. |4 aut | |
| 776 | 0 | |t Supervised Learning with Complex-valued Neural Networks |b Texte imprimé |z 9783642294907 | |
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