|
Fully Coupled and Feedforward Neural Networks with Complex-valued Neurons| old_uid | 2794 |
|---|
| title | Fully Coupled and Feedforward Neural Networks with Complex-valued Neurons |
|---|
| start_date | 2007/05/10 |
|---|
| schedule | 10h |
|---|
| online | no |
|---|
| location_info | salle 549 |
|---|
| summary | This talk introduces a definition of complex-valued neurons with discrete outputs. It covers a novel method of their applications in fully coupled associative memories. Such memories are able to process multiple gray levels when applied for image de-noising. In addition, complex-valued neurons can be generalized to take a continuum of values. Learning of such neurons is demonstrated and described in the context of traditional multilayer feedforward network learning. Such learning is derivative-free and it usually requires reduced network architecture. Selected examples and applications of such networks are also discussed. |
|---|
| responsibles | Bouchon-Meunier, Diaz, Gallinari |
|---|
| |
|