Optimal FPGA implementation of GAMLP systems
| Autor: | I.C. Rincu, I. Nicolaescu, A. Radu, Iulian-Constantin Vizitiu, Florin Popescu |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
Hardware architecture
Quantitative Biology::Neurons and Cognition Artificial neural network business.industry Computer science Time delay neural network Computer Science::Neural and Evolutionary Computation Machine learning computer.software_genre Statistical classification ComputingMethodologies_PATTERNRECOGNITION Logic synthesis Automatic target recognition Computer engineering Pattern recognition (psychology) Artificial intelligence business Field-programmable gate array computer |
| Zdroj: | 2010 12th International Conference on Optimization of Electrical and Electronic Equipment. |
| DOI: | 10.1109/optim.2010.5510377 |
| Popis: | An interesting approach to assure the real-time property of neural automatic target recognition systems is to use an efficient hardware implementation of the neural networks used inside of their classification chains. Consequently, a proper genetic procedure used to optimize both connectivity and distribution of the neural weights of MLP neural networks (GAMLP system) is presented. Finally, having as starting point the previous broached aspects, an optimal FPGA hardware implementation of MLP neural networks is also described. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|