Motor Control and Learning by the State Space Model

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6927

Full metadata record

DC Field	Value	Language
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	-
Appears in Collections:	MIT Items

Files in This Item:

There are no files associated with this item.

DSpace JSPUI