Notes on the Extended Class of Stein Estimators

1986 ◽  
Author(s):  
Suk-Ki Hahn
Keyword(s):  
Extended Class

An extended class of matched pairs tests based on powers of ranks

Psychometrika ◽  
1976 ◽  
Vol 41 (1) ◽  
pp. 89-100 ◽  
Author(s):  
Paul W. Mielke ◽  
Kenneth J. Berry
Keyword(s):  
Matched Pairs ◽  
Extended Class

On the Extended Class of SUPM and Their Generating URSM Over Non-Archimedean Field

2021 ◽  
Vol 13 (3) ◽  
pp. 175-185
Author(s):  
Abhijit Banerjee ◽  
Sayantan Maity
Keyword(s):  
Extended Class

scholarly journals On an extended class of error-locating codes

1965 ◽  
Vol 8 (2) ◽  
pp. 163-169 ◽  
Author(s):  
Jack K. Wolf
Keyword(s):  
Extended Class

ON CONTINUOUSLY-GENERATED SELF-SIMILAR MULTIFRACTALS

Fractals ◽  
2001 ◽  
Vol 09 (02) ◽  
pp. 129-147 ◽  
Author(s):  
THIERRY HUILLET ◽  
ANNA PORZIO
Keyword(s):  
Self Similar ◽  
Extended Class

An extended class of "continuously-generated and deterministic" multifractals with some features common to the ones of "random" multifractals is investigated.

Parameter Estimation of Maneuvering Variables of SIGMA-Extended War Ship Using Kalman Filter

2018 ◽  
Vol 874 ◽  
pp. 96-102
Author(s):  
Aulia Siti Aisjah ◽  
Agoes Ahmad Masroeri ◽  
Nathanael Leon Gozali ◽  
Ridho Akbar ◽  
Devina Permata Sari ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Kalman Filter ◽  
Control System ◽  
Absolute Error ◽  
Sea State ◽  
Set Point ◽  
Extended Class ◽  
A Performance

SIGMA-class warship one of warship type is designed up to sea state 6. The ship was redesigned in enlarged dimensions, and called SIGMA extended class warships. A control system can give a performance of response in accordance to the set point when the value of controlled variable can be transmitted to the controller accurately. The characteristic of sensor is not usually able to tranmit a proper value, due to the noise on the sensor and also the environment disturbances. This paper describe a strategy of Kalman filter to estimate variables controlled when the presence noise on the compass or gyrocompas. The result of Kalman filter implementations give the magnitude of the integral absolute error of yaw and sway less than 5%, when there are noise on the measurement and the disturbances.

Fundamental Solution via Invariant Approach for a Brain Tumor Model and its Extensions

2014 ◽  
Vol 69 (12) ◽  
pp. 725-732 ◽  
Author(s):  
Andrew G. Johnpillai ◽  
Fazal M. Mahomed ◽  
Saeid Abbasbandy
Keyword(s):  
Brain Tumor ◽  
Partial Differential Equations ◽  
Fundamental Solution ◽  
Differential Equations ◽  
Closed Form Solution ◽  
Form Solution ◽  
Tumor Models ◽  
Partial Differential ◽  
Equivalence Transformations ◽  
Extended Class

AbstractWe firstly show how one can use the invariant criteria for a scalar linear (1+1) parabolic partial differential equations to perform reduction under equivalence transformations to the first Lie canonical form for a class of brain tumor models. Fundamental solution for the underlying class of models via these transformations is thereby found by making use of the well-known fundamental solution of the classical heat equation. The closed-form solution of the Cauchy initial value problem of the model equations is then obtained as well. We also demonstrate the utility of the invariant method for the extended form of the class of brain tumor models and find in a simple and elegant way the possible forms of the arbitrary functions appearing in the extended class of partial differential equations. We also derive the equivalence transformations which completely classify the underlying extended class of partial differential equations into the Lie canonical forms. Examples are provided as illustration of the results.

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