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dc.contributor.authorRaibert, Marc H.en_US
dc.date.accessioned2004-10-20T20:08:02Z
dc.date.available2004-10-20T20:08:02Z
dc.date.issued1977-09-01en_US
dc.identifier.otherAITR-439en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/6927
dc.description.abstractA 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.extent13850748 bytes
dc.format.extent10963405 bytes
dc.format.mimetypeapplication/postscript
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.relation.ispartofseriesAITR-439en_US
dc.titleMotor Control and Learning by the State Space Modelen_US


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