scholarly journals Numerical estimation on the threshold of nerve excitation phenomena by the application of current with multiple frequencies based on Frankenhaeuser‐Huxley model

2020 ◽  
Vol 103 (5-6) ◽  
pp. 22-29
Author(s):  
Kei Makino ◽  
Yukihisa Suzuki ◽  
Masao Taki
Keyword(s):  
Numerical Estimation ◽  
Multiple Frequencies ◽  
Nerve Excitation

Under- and Over-Estimation

2011 ◽  
Vol 58 (1) ◽  
pp. 39-49 ◽  
Author(s):  
Virginie Crollen ◽  
Julie Castronovo ◽  
Xavier Seron
Keyword(s):  
Empirical Data ◽  
Accurate Estimation ◽  
Numerical Estimation ◽  
Production Task ◽  
Estimation Task ◽  
Reproduction Task ◽  
Perception Task ◽  
Adult Participants ◽  
Mapping Hypothesis ◽  
Task Perception

Over the last 30 years, numerical estimation has been largely studied. Recently, Castronovo and Seron (2007) proposed the bi-directional mapping hypothesis in order to account for the finding that dependent on the type of estimation task (perception vs. production of numerosities), reverse patterns of performance are found (i.e., under- and over-estimation, respectively). Here, we further investigated this hypothesis by submitting adult participants to three types of numerical estimation task: (1) a perception task, in which participants had to estimate the numerosity of a non-symbolic collection; (2) a production task, in which participants had to approximately produce the numerosity of a symbolic numerical input; and (3) a reproduction task, in which participants had to reproduce the numerosity of a non-symbolic numerical input. Our results gave further support to the finding that different patterns of performance are found according to the type of estimation task: (1) under-estimation in the perception task; (2) over-estimation in the production task; and (3) accurate estimation in the reproduction task. Moreover, correlation analyses revealed that the more a participant under-estimated in the perception task, the more he/she over-estimated in the production task. We discussed these empirical data by showing how they can be accounted by the bi-directional mapping hypothesis ( Castronovo & Seron, 2007 ).

Numerical estimation of volatility values from discretely observed diffusion data

2006 ◽  
Vol 9 (4) ◽  
pp. 1-36 ◽  
Author(s):  
Jakša Cvitanic ◽  
Boris Rozovskii ◽  
Ilya Zaliapin
Keyword(s):  
Numerical Estimation ◽  
Diffusion Data

Radiometric resolution and dynamic range of aerial and space images, obtained for monitoring and mapping purposes

2020 ◽  
Vol 964 (10) ◽  
pp. 40-48
Author(s):  
I.A. Anikeeva
Keyword(s):  
Dynamic Range ◽  
Numerical Estimation ◽  
Space Images

The dynamic range and radiometric resolution are among the most important indicators of aerial and space images’ fine quality. Gradation properties are of particular importance for aerial and space images, obtained for monitoring and mapping purposes, because the completeness and quality of the information on the earth’s surface objects depend on them, the accuracy of brightness features reproduction of earth’s surface objects. The author discusses various approaches to defining the concepts of dynamic range and radiometric resolution; the most proper definitions of these terms are given in the context of estimating the image’s gradation properties. The expediency of separating the concepts of nominal, actual and useful (effective) radiometric resolution is shown; their definitions are given. Methods of dynamic range and radio-metric resolution numerical estimation based on a histogram are shown. Absolute and relative indicators are considered. The advantages of using relative indicators are shown. Examples of the dynamic range and radiometric resolution evaluation are given basing upon the images obtained by ‘‘Canopus-B’’ spacecraft.

scholarly journals A Novel Global Sensitivity Measure Based on Probability Weighted Moments

Symmetry ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 90
Author(s):  
Shufang Song ◽  
Lu Wang
Keyword(s):  
Sensitivity Analysis ◽  
Global Sensitivity Analysis ◽  
Small Samples ◽  
Double Loop ◽  
Numerical Estimation ◽  
Global Sensitivity ◽  
Sensitivity Measure ◽  
Probability Weighted Moments ◽  
Input Variables ◽  
Single Set

Global sensitivity analysis (GSA) is a useful tool to evaluate the influence of input variables in the whole distribution range. Variance-based methods and moment-independent methods are widely studied and popular GSA techniques despite their several shortcomings. Since probability weighted moments (PWMs) include more information than classical moments and can be accurately estimated from small samples, a novel global sensitivity measure based on PWMs is proposed. Then, two methods are introduced to estimate the proposed measure, i.e., double-loop-repeated-set numerical estimation and double-loop-single-set numerical estimation. Several numerical and engineering examples are used to show its advantages.

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