Results 321 to 330 of about 6,561,703 (356)

Reward positivity: Reward prediction error or salience prediction error?

Psychophysiology, 2016
AbstractThe reward positivity is a component of the human ERP elicited by feedback stimuli in trial‐and‐error learning and guessing tasks. A prominent theory holds that the reward positivity reflects a reward prediction error signal that is sensitive to outcome valence, being larger for unexpected positive events relative to unexpected negative events (
Sepideh, Heydari, Clay B, Holroyd
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Prediction of the Probable Errors of Predictions

Monthly Weather Review, 1985
Abstract We propose here a method of “stochastic-dynamic” prediction that is computationally more efficient than integration of the full set of “second-moment” equations. This gain is achieved by omitting covariances between modes in different interacting triads, and by expressing intratriad covariances in terms of error variances, via the conditions ...
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On the Error of Prediction of a Time Series

Biometrika, 1972
Abstract : Parametric and nonparametric procedures for the prediction of a time series are discussed. In each case the increase in the mean squared error of prediction over its minimum level due to the use of estimated spectra is assessed. The fitting of simple parametric models as approximations is also discussed. (Author)
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Error significance but not error expectancy predicts error-related negativities for different error types

Behavioural Brain Research, 2016
Violations of outcome expectancies have been proposed to account for error-related brain activity in the medial prefrontal cortex. The present study investigated whether early error monitoring processes are sensitive only to the expectancy of errors, or whether these processes also evaluate the significance of errors.
Martin E. Maier, Marco Steinhauser
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On the Asymptotic Behavior of the Prediction Error

Theory of Probability & Its Applications, 1964
Let $\{ {x_j } \}$ be a stationary stochastic process in the wide sense which is regular, with spectral density function $f(\lambda )$. Denote by $\sigma _n^2 $ the mean square prediction error in predicting $x_0 $ by linear forms in $x_{ - 1} ,x_{ - 2} , \cdots ,x_{ - n} $.
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Error Prediction for Multi-Classification

Sixth International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing and First ACIS International Workshop on Self-Assembling Wireless Networks (SNPD/SAWN'05), 2005
This paper describes an error prediction mechanism for multiclassification systems. First, a multiclassification system is constructed by combining a suite of two-class classifiers. While training, each sub-classifier does not utilize all the training data and the remaining data are used for testing purpose.
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Maximum likelihood and prediction error methods

Automatica, 1979
Abstract The basic ideas behind the parameter estimation methods are discussed in a general setting. The application to estimation or parameters in dynamical systems is treated in detail using the prototype problem of estimating parameters in a continuous time system using discrete time measurements. Computational aspects are discussed.
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A New assembly precision prediction method of aeroengine high-pressure rotor system considering manufacturing error and deformation of parts

Journal of Manufacturing Systems, 2021
Xiaokai Mu, Yunlong Wang
exaly  

An ensemble method for short-term wind power prediction considering error correction strategy

Applied Energy, 2022
Lin Ye, Binhua Dai, Ming Pei
exaly  

A Novel Wind Speed Interval Prediction Based on Error Prediction Method

IEEE Transactions on Industrial Informatics, 2020
Geng Tang, Chaoshun Li, Pak Kin Wong
exaly