Name
Abstract | ||
|---|---|---|
One important step towards the cognitive neural prosthesis design is to achieve real-time prediction of neuronal firing pattern. An FPGA-based hardware computational platform is designed to guarantee this hard real-time signal processing requirement. The proposed platform can work in dual modes: generalized Laguerre-Volterra model parameters estimation and output prediction, and can switch between these two important system functions. Compared with the traditional software-based platform implemented in C, the hardware platform achieves better efficiency in doing the biocomputations by up to thousandfold speedup in this process. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/EMBC.2012.6346986 | EMBC |
Keywords | Field | DocType |
neuronal firing pattern,cognitive neural prosthesis design,neurophysiology,dual mode fpga design,prosthetics,generalized laguerre-volterra model parameters estimation,cognitive systems,hippocampal prosthesis,field programmable gate arrays,output prediction | Signal processing,Hippocampal prosthesis,Computer science,Cognitive systems,Neural Prosthesis,Field-programmable gate array,Fpga design,Electronic engineering,Software,Speedup | Conference |
Volume | ISSN | ISBN |
2012 | 1557-170X | 978-1-4577-1787-1 |
Citations | PageRank | References |
2 | 0.38 | 4 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Will X. Y. Li | 1 | 45 | 7.08 |
| Rosa H M Chan | 2 | 182 | 22.79 |
| Dong Song | 3 | 202 | 34.25 |
| Theodore W Berger | 4 | 2 | 0.38 |
| Ray C. C. Cheung | 5 | 625 | 72.26 |