Name
Title | ||
|---|---|---|
EMG prediction from motor cortical recordings via a nonnegative point-process filter. |
Abstract | ||
|---|---|---|
A constrained point-process filtering mechanism for prediction of electromyogram (EMG) signals from multichannel neural spike recordings is proposed here. Filters from the Kalman family are inherently suboptimal in dealing with non-Gaussian observations, or a state evolution that deviates from the Gaussianity assumption. To address these limitations, we modeled the non-Gaussian neural spike train ... |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/TBME.2011.2159115 | IEEE Transactions on Biomedical Engineering |
Keywords | Field | DocType |
Electromyography,Kalman filters,Neurons,History,Muscles,Delay,Computational modeling | Nonlinear system,Computer science,Point process,Causal filter,Artificial intelligence,Computer vision,Spike train,Neurophysiology,Pattern recognition,Linear model,Filter (signal processing),Speech recognition,Kalman filter | Journal |
Volume | Issue | ISSN |
59 | 7 | 0018-9294 |
Citations | PageRank | References |
6 | 0.57 | 6 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kianoush Nazarpour | 1 | 75 | 19.08 |
| Christian Ethier | 2 | 6 | 1.58 |
| Liam Paninski | 3 | 926 | 99.30 |
| James M Rebesco | 4 | 6 | 0.57 |
| R Chris Miall | 5 | 68 | 7.16 |
| Lee E. Miller | 6 | 27 | 5.23 |