scholarly journals Influence of 14C Concentration Changes in the Past On Statistical Inference of Time Intervals

Radiocarbon ◽  
2004 ◽  
Vol 46 (2) ◽  
pp. 997-1004 ◽  
Author(s):  
Adam Michczyński
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Statistical Inference ◽  
Real Time ◽  
Density Function ◽  
Calibration Curve ◽  
Time Interval ◽  
Time Intervals ◽  
The Real ◽  
Concentration Changes

The influence of the calibration curve on the statistical inference of time intervals was investigated. For this purpose, the calculation of the summed probability density function was used. Computer simulations were done for batches of 11 samples, each time uniformly covering 200-yr time intervals. The results show that the calibration curve causes the summed probability density function of a group to cover a wider interval than the real-time interval of the phenomenon. Moreover, the estimated time interval may be often shifted in relation to the real-time interval.

scholarly journals The Droplike Nature of Rain and Its Invariant Statistical Properties

2009 ◽  
Vol 10 (1) ◽  
pp. 79-95 ◽  
Author(s):  
Massimiliano Ignaccolo ◽  
Carlo De Michele ◽  
Simone Bianco
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Moving Average ◽  
Small Diameter ◽  
Time Intervals ◽  
Drop Time ◽  
Two Phases ◽  
Invariant Properties ◽  
Invariant Shape

Abstract This study looks for statistically invariant properties of the sequences of inter-drop time intervals and drop diameters. The authors provide evidence that these invariant properties have the following characteristics: 1) large inter-drop time intervals (≳10 s) separate drops of small diameter (≲0.6 mm); 2) the rainfall phenomenon has two phases: a quiescent phase, whose contribution to the total cumulated flux is virtually null, and an active, nonquiescent, phase that is responsible for the bulk of the precipitated volume; 3) the probability density function of inter-drop time intervals has a power-law-scaling regime in the range of ∼1 min and ∼3 h); and 4) once the moving average and moving standard deviation are removed from the sequence of drop diameters, an invariant shape emerges for the probability density function of drop diameters during active phases.

scholarly journals An inequality for probability density functions arising from a distinguishability problem

1998 ◽  
Vol 39 (3) ◽  
pp. 350-354
Author(s):  
Boris Guljaš ◽  
C. E. M. Pearce ◽  
Josip Pečarić
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Real Line ◽  
Integral Inequality ◽  
Probability Density Functions ◽  
Density Functions ◽  
The Real ◽  
Image Position

AbstractAn integral inequality is established involving a probability density function on the real line and its first two derivatives. This generalizes an earlier result of Sato and Watari. If f denotes the probability density function concerned, the inequality we prove is thatunder the conditions β > α 1 and 1/(β+1) < γ ≤ 1.

scholarly journals ESTIMATION OF QUALITY PARAMETERS IN THE RADIO FLIGHT SUPPORT OPERATIONAL SYSTEM

Aviation ◽  
2016 ◽  
Vol 20 (3) ◽  
pp. 123-128 ◽  
Author(s):  
Oleksandr SOLOMENTSEV ◽  
Maksym ZALISKYI ◽  
Oleksiy ZUIEV
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Finite Time ◽  
Quality Parameters ◽  
Time Interval ◽  
Finite Time Interval ◽  
Operational System ◽  
Radio Equipment ◽  
Probability Density Function Pdf

The paper considers the structure of the operational system of radio equipment, determines the procedures related to the estimation of the quality parameters in the radio flight support operational system, using the ready-to-operate factor and the probability of no failure operation in a finite time interval, and shows the analytical ratios for the probability density function (PDF).

Adaptive Interacting Multiple Model Unscented Particle Filter Tracking Algorithm

2012 ◽  
Vol 190-191 ◽  
pp. 906-910 ◽  
Author(s):  
Hong Jiang Liu
Keyword(s):  
Probability Density Function ◽  
Particle Filter ◽  
Probability Density ◽  
Real Time ◽  
Density Function ◽  
Tracking System ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Tracking Accuracy ◽  
Unscented Particle Filter

In order to study the tracking problem of maneuvering image sequence target in complex environment with multi-sensor array, the adaptive interacting multiple model unscented particle filter algorithm based on measured residual is proposed. The motion array tracking system dynamic model is established, and initialized probability density function also is defined based on unscented transformation, after that, the measured covariance and state covariance are online adjusted by measured residual and adaptive factor, then the self-adapting capability of filter gain and the real-time capability of posterior probability density function are improved. Finally, the simulation results between different algorithms show the validity and superiority of the presented algorithm in tracking accuracy, stability and real-time capability.

scholarly journals Methods for modeling the active surface of grinding wheels

Mechanik ◽  
2018 ◽  
Vol 91 (10) ◽  
pp. 907-914 ◽  
Author(s):  
Wojciech Kacalak ◽  
Filip Szafraniec ◽  
Dariusz Lipiński
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Active Surface ◽  
Grinding Wheel ◽  
Real Surface ◽  
Grinding Wheels ◽  
Wheel Surface ◽  
The Real

This paper many different methods of generating the topography of the grinding wheel surface and the methodology for assessing the compatibility of models with the surface of real tools was presented. The methodology was indicated that certain features regarding the shape and position of the highest vertices are decisive for assessing the model’s conformity with the real surface of the grinding wheel. The significance of not only the form of the distribution of the vertices of the grains was emphasized, but also the significance of the fragment of the probability density function relating to the highest vertices and the autocorrelation of the vertex position as the most important feature, which often are overlooked in the models described in the literature.

Adaptive Interacting Multiple Model Unscented Particle Filter for Dynamic Acoustic Array

2013 ◽  
Vol 300-301 ◽  
pp. 407-413
Author(s):  
Ya Lei Liu ◽  
Xiao Hui Gu
Keyword(s):  
Probability Density Function ◽  
Particle Filter ◽  
Probability Density ◽  
Real Time ◽  
Density Function ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Tracking Accuracy ◽  
Unscented Particle Filter ◽  
Acoustic Array

Abstract. In order to improve the tracking accuracy of 3D dynamic acoustic array to 2D maneuvering target in colored noise environment, the adaptive interacting multiple model unscented particle filter algorithm based on measured residual is proposed. The 3D motion acoustic array tracking system dynamic model is established, and initialized probability density function also is defined based on unscented transformation, after that, the measured covariance and state covariance are online adjusted by measured residual and adaptive factor, then the self-adapting capability of filter gain and the real-time capability of posterior probability density function are improved. Finally, the simulation results between different algorithms show the validity and superiority of the presented algorithm in tracking accuracy, stability and real-time capability.

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