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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. ...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2013.
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| Edición: | 1st ed. 2013. |
| Colección: | Studies in Computational Intelligence,
421 |
| Temas: | |
| Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- 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).