Identification of a Deterministic Wiener System Based on Input Prediction Error

2020 ◽  
Author(s):  
Shaoxue Jing
Keyword(s):  
Prediction Error ◽  
Wiener System ◽  
Input Prediction

How Could We Get Nosology from Computation?

2016 ◽  
Author(s):  
Christoph Mathys
Keyword(s):  
Bayesian Inference ◽  
Conceptual Framework ◽  
Systems Theory ◽  
Prediction Error ◽  
Inductive Logic ◽  
Prediction Errors ◽  
Future Directions ◽  
The Difference ◽  
The Mind ◽  
Input Prediction

Psychiatry has found it difficult to develop a nosology that allows for the targeted treatment of disorders of the mind. This article sets out a possible way forward: harnessing systems theory to provide the conceptual constraints needed to link clinical phenomena with neurobiology. This approach builds on the insight that the mind is a system which, to regulate its environment, needs to have a model of that environment and needs to update predictions about it using the rules of inductive logic. It can be shown that Bayesian inference can be reduced to updating beliefs based on precision-weighted prediction errors, where a prediction error is the difference between actual and predicted input, and precision is the confidence associated with the input prediction. Precision weighting of prediction errors entails that a given discrepancy between outcome and prediction means more, and leads to greater belief updates, the more confidently the prediction was made. This provides a conceptual framework linking clinical experience with the pathophysiology underlying disorders of the mind. Limitations of this approach are discussed and ways to work around them illustrated. Initial steps and possible future directions toward a nosology based on failures of precision weighting are discussed.

Temporal dynamics of real-world emotion are more strongly linked to prediction error than outcome.

2020 ◽  
Vol 149 (9) ◽  
pp. 1755-1766 ◽  
Author(s):  
William J. Villano ◽  
A. Ross Otto ◽  
C. E. Chiemeka Ezie ◽  
Roderick Gillis ◽  
Aaron S. Heller
Keyword(s):  
Real World ◽  
Prediction Error ◽  
Temporal Dynamics

THE INFLUENCE OF THE WIND SPEED PREDICTION ERROR ON THE SIZE OF THE STORAGE CONTROLLED OPERATION ZONE IN THE SYSTEM WITH THE WIND GENERATOR

2020 ◽  
Vol 2020 (57) ◽  
pp. 35-41
Author(s):  
K.S. Klen ◽  
◽  
M.K. Yaremenko ◽  
V.Ya. Zhuykov ◽  
◽  
...  
Keyword(s):  
Wind Speed ◽  
Prediction Error ◽  
Average Energy ◽  
Interpolation Formula ◽  
Wind Speed Prediction ◽  
Wind Generator ◽  
Prediction Horizon ◽  
Speed Prediction ◽  
Using Data ◽  
Predictor Corrector

The article analyzes the influence of wind speed prediction error on the size of the controlled operation zone of the storage. The equation for calculating the power at the output of the wind generator according to the known values of wind speed is given. It is shown that when the wind speed prediction error reaches a value of 20%, the controlled operation zone of the storage disappears. The necessity of comparing prediction methods with different data discreteness to ensure the minimum possible prediction error and determining the influence of data discreteness on the error is substantiated. The equations of the "predictor-corrector" scheme for the Adams, Heming, and Milne methods are given. Newton's second interpolation formula for interpolation/extrapolation is given at the end of the data table. The average relative error of MARE was used to assess the accuracy of the prediction. It is shown that the prediction error is smaller when using data with less discreteness. It is shown that when using the Adams method with a prediction horizon of up to 30 min, within ± 34% of the average energy value, the drive can be controlled or discharged in a controlled manner. References 13, figures 2, tables 3.

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