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Hardware spiking neural networks: parallel implementations using FPGAs
| Content Provider | Semantic Scholar |
|---|---|
| Author | Bakó, László Brassai, Sándor Tihamér |
| Copyright Year | 2006 |
| Abstract | Neuromorphic neural networks are of interest both from a biological point of view and in terms of robust signaling in noisy environments. The basic question however, is what type of architecture can be used to efficiently build such neural networks in hardware devices, in order to use them in real time process control problems. In this paper a novel, hardware implementation friendly, "pulse reactive" model of spiking neurons is described. This is used then to implement a fully connected network, yielding a high degree of parallelism. The modular neuron structure, acquired signals and a process control application are given. |
| Starting Page | 261 |
| Ending Page | 266 |
| Page Count | 6 |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.wseas.us/e-library/conferences/2006prague/papers/514-219.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
