Name
Abstract | ||
|---|---|---|
If we can estimate the transition of biomedical system from biomedical signals, it can be very useful in increasing the safety of medical treatment. And so, The examination was performed aiming at estimation of the transition and parameter change of some parametric models such as time-variant linear model and time-variant nonlinear model. In this study, we devised an evaluation index using BP Neural Networks as the technique to detect the transition and the parameter change from the measured data. As results of computer simulations, the availability of system identification of the proposed method was confirmed. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-30133-2_141 | LECTURE NOTES IN COMPUTER SCIENCE |
Keywords | Field | DocType |
linear model,neural network,time series model,system identification,computer simulation,parametric model,indexation | Time series,Parametric model,Pattern recognition,Computer science,Linear model,Nonlinear system identification,Medical treatment,Artificial intelligence,Artificial neural network,System identification,Nonlinear model,Machine learning | Conference |
Volume | ISSN | Citations |
3214 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 1 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Takahiro Emoto | 1 | 4 | 4.93 |
| Akutagawa Masatake | 2 | 13 | 11.43 |
| Hirofumi Nagashino | 3 | 6 | 7.07 |
| Y. Kinouchi | 4 | 22 | 16.80 |