Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12202/3995
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dc.contributor.authorReinstein, Aryeh
dc.date.accessioned2018-10-18T15:10:28Z
dc.date.available2018-10-18T15:10:28Z
dc.date.issued2010-09
dc.identifier.urihttps://hdl.handle.net/20.500.12202/3995
dc.identifier.urihttps://ezproxy.yu.edu/login?url=https://repository.yu.edu/handle/20.500.12202/3995
dc.descriptionThe file is restricted for YU community access only.en_US
dc.descriptionThe file is restricted for YU community access only.
dc.description.abstractWe take motion for granted. As you flipped the cover page to this paper or scrolled down on your computer screen by moving a computer mouse, you probably did not calculate the exact trajectory of your hand and think about the exact muscle contractions needed to execute that specific course of action. And yet we perform simple actions such as these constantly. When we decide that we want to move in a certain way, the amazing computational machines that are our brains are somehow able to subconsciously calculate the precise muscle contractions needed to achieve that motion. The human brain, and in fact, the brain of all animals, is an expert in solving the control problem: determining the required input parameters for the system’s variables and deriving the values required for those parameters to achieve a desired outcome. Put more simply, we subconsciously figure out which muscles need to be contracted or relaxed and the exact extent of that change that is required.en_US
dc.description.sponsorshipJay and Jeanie Schottenstein Honors Programen_US
dc.publisherYeshiva Collegeen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectOctopuses -- Locomotion -- Researchen_US
dc.subjectExtremities (Anatomy) -- Mechanical propertiesen_US
dc.subjectAnimal locomotionen_US
dc.titleA Forward Analytic Model for the Control of Octopus Arm Movementsen_US
dc.typeThesisen_US
Appears in Collections:Jay and Jeanie Schottenstein Honors Student Theses

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