A proof of the minimal-phase property of the prediction-error filter

1983 ◽  
Vol 71 (7) ◽  
pp. 905-905
Author(s):  
S.J. Orfanidis
Keyword(s):  
Prediction Error ◽  
Phase Property ◽  
Minimal Phase

scholarly journals On the minimum phase property of prediction-error polynomials

1997 ◽  
Vol 4 (5) ◽  
pp. 126-127 ◽  
Author(s):  
P.P. Vaidyanathan ◽  
J. Tuqan ◽  
A. Kirac
Keyword(s):  
Prediction Error ◽  
Minimum Phase ◽  
Phase Property

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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