Complex-Valued Neural Networks with Multi-Valued Neurons
Complex-Valued Neural Networks have higher functionality, learn faster and generalize better than their real-valued counterparts. This book is devoted to the Multi-Valued Neuron (MVN) and MVN-based neural networks. It contains a comprehensive observation of MVN theory, its learning, and applications...
Enregistré dans:
| Auteur principal: | |
|---|---|
| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Édition: | 1st ed. 2011. |
| Collection: | Studies in Computational Intelligence
353 |
| Accès en ligne: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Complex-Valued Neural Networks with Multi-Valued Neurons, Texte imprimé, 9783642203527 • Complex-Valued Neural Networks with Multi-Valued Neurons, Texte imprimé, 9783642203527 • Complex-Valued Neural Networks with Multi-Valued Neurons, Texte imprimé, 9783642203541 • Complex-Valued Neural Networks with Multi-Valued Neurons, Texte imprimé, 9783662506318 |
| LEADER | 04218nam a22003617a 4500 | ||
|---|---|---|---|
| 001 | 973521 | ||
| 008 | 111115q2000 xx ||| |||| 00| 0 eng d | ||
| 009 | PPN156315963 | ||
| 020 | |a 9783642203534 | ||
| 041 | 0 | |a eng | |
| 082 | |a 006.3 | ||
| 100 | 1 | |a Aizenberg, Igor. | |
| 245 | 1 | 0 | |a Complex-Valued Neural Networks with Multi-Valued Neurons |c by Igor Aizenberg. |
| 250 | |a 1st ed. 2011. | ||
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Studies in Computational Intelligence |v 353 |x 1860-9503 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a Why We Need Complex-Valued Neural Networks? The Multi-Valued Neuron MVN Learning Multilayer Feedforward Neural Network based on Multi-Valued Neurons (MLMVN) Multi-Valued Neuron with a Periodic Activation Function Applications of MVN and MLMVN | |
| 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 Complex-Valued Neural Networks have higher functionality, learn faster and generalize better than their real-valued counterparts. This book is devoted to the Multi-Valued Neuron (MVN) and MVN-based neural networks. It contains a comprehensive observation of MVN theory, its learning, and applications. MVN is a complex-valued neuron whose inputs and output are located on the unit circle. Its activation function is a function only of argument (phase) of the weighted sum. MVN derivative-free learning is based on the error-correction rule. A single MVN can learn those input/output mappings that are non-linearly separable in the real domain. Such classical non-linearly separable problems as XOR and Parity n are the simplest that can be learned by a single MVN. Another important advantage of MVN is a proper treatment of the phase information. These properties of MVN become even more remarkable when this neuron is used as a basic one in neural networks. The Multilayer Neural Network based on Multi-Valued Neurons (MLMVN) is an MVN-based feedforward neural network. Its backpropagation learning algorithm is derivative-free and based on the error-correction rule. It does not suffer from the local minima phenomenon. MLMVN outperforms many other machine learning techniques in terms of learning speed, network complexity and generalization capability when solving both benchmark and real-world classification and prediction problems. Another interesting application of MVN is its use as a basic neuron in multi-state associative memories. The book is addressed to those readers who develop theoretical fundamentals of neural networks and use neural networks for solving various real-world problems. It should also be very suitable for Ph.D. and graduate students pursuing their degrees in computational intelligence | ||
| 776 | 0 | |t Complex-Valued Neural Networks with Multi-Valued Neurons |b Texte imprimé |z 9783642203527 | |
| 776 | 0 | |t Complex-Valued Neural Networks with Multi-Valued Neurons |b Texte imprimé |z 9783642203527 | |
| 776 | 0 | |t Complex-Valued Neural Networks with Multi-Valued Neurons |b Texte imprimé |z 9783642203541 | |
| 776 | 0 | |t Complex-Valued Neural Networks with Multi-Valued Neurons |b Texte imprimé |z 9783662506318 | |
| 856 | 4 | |q PDF |u https://doi.org/10.1007/978-3-642-20353-4 |z Accès sur la plateforme de l'éditeur | |
| 856 | 4 | |u https://revue-sommaire.istex.fr/ark:/67375/8Q1-KQH1T57G-6 |z Accès sur la plateforme Istex | |
| 856 | 4 | |5 452349901:750611650 |u https://ezproxy.univ-orleans.fr/login?url=https://dx.doi.org/10.1007/978-3-642-20353-4 |z Accès Université d'Orléans | |
| 856 | 4 | |5 180339901:753970767 |u https://ezproxy.insa-cvl.fr/login?qurl=https://dx.doi.org/10.1007/978-3-642-20353-4 |z Accès INSA CVL | |
| 997 | |0 973521 |1 Livre numérique |a Ressource numérique |b INSA |b ENSA |c 0/Bibliothèque numérique/ |c 1/Bibliothèque numérique/Autre ressource numérique/ | ||