Motor Control and Learning by the State Space Model

dc.creator	Raibert, Marc H.
dc.date	2004-10-20T20:08:02Z
dc.date	2004-10-20T20:08:02Z
dc.date	1977-09-01
dc.date.accessioned	2013-10-09T02:47:37Z
dc.date.available	2013-10-09T02:47:37Z
dc.date.issued	2013-10-09
dc.identifier	AITR-439
dc.identifier	http://hdl.handle.net/1721.1/6927
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description	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.
dc.format	13850748 bytes
dc.format	10963405 bytes
dc.format	application/postscript
dc.format	application/pdf
dc.language	en_US
dc.relation	AITR-439
dc.title	Motor Control and Learning by the State Space Model

Files in this item

Files	Size	Format	View
There are no files associated with this item.