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In particular, we suggest a system that responds to sensory prediction error and learns the structure of the sensory-motor dynamic environment ("fast system"), while another system responds to task performance error and learns the elements needed to perform a task ("slow system").
Differences were evaluated using standard statistical performance error measurements (median performance error (PE) <5%).
Each controller was tested in 1000 simulated patients, and control performance was assessed by calculating the median performance error (MDPE), median absolute performance error (MDAPE), Wobble, and Divergence for each controller group.
The median absolute performance error was 17 (10, 24) in the N2O and 22 (128 28) in Air trial.
The median(25th, 75th percentiles) of the median performance error was -13 (-24, -1) during the N2O and -18 (-26, -9) during the Air trial.
During GPS outages, the radial basis function neural network can provide high performance error estimation for position and velocity to improve state information.
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For learning to occur through trial and error, the nervous system must effectively detect and encode performance errors.
Performance errors determine the ability of a particular op-amp to meet its desired accuracy requirement.
Decreased electrodermal activity in the ADHD group also suggested a motivational insensitivity to performance errors.
Particularly under varying workload conditions, temporal distortions may lead to performance errors.
Pipelines constructed using modular components have very brittle performance: errors in earlier components cascade through the pipeline causing catastrophic failures in the eventual output.
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