Motor Control and Learning by the State Space Model
| dc.date.accessioned | 2004-10-20T20:08:02Z | |
| dc.date.accessioned | 2018-11-24T10:22:29Z | |
| dc.date.available | 2004-10-20T20:08:02Z | |
| dc.date.available | 2018-11-24T10:22:29Z | |
| dc.date.issued | 1977-09-01 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1721.1/6927 | |
| dc.identifier.uri | http://repository.aust.edu.ng/xmlui/handle/1721.1/6927 | |
| dc.description.abstract | A model is presented that deals with problems of motor control, motor learning, and sensorimotor integration. The equations of motion for a limb are parameterized and used in conjunction with a quantized, multi-dimensional memory organized by state variables. Descriptions of desired trajectories are translated into motor commands which will replicate the specified motions. The initial specification of a movement is free of information regarding the mechanics of the effector system. Learning occurs without the use of error correction when practice data are collected and analyzed. | en_US |
| dc.format.extent | 13850748 bytes | |
| dc.format.extent | 10963405 bytes | |
| dc.language.iso | en_US | |
| dc.title | Motor Control and Learning by the State Space Model | en_US |
Files in this item
| Files | Size | Format | View |
|---|---|---|---|
| AITR-439.pdf | 10.96Mb | application/pdf | View/ |
| AITR-439.ps | 13.85Mb | application/postscript | View/ |