Statistical method for determination of interspike interval probability density function

2008 ◽  
Author(s):  
J. Minich ◽  
L. Negyessy ◽  
P. Barone ◽  
E. Procyk ◽  
L. Zalanyi ◽  
...  
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Statistical Method ◽  
Density Function ◽  
Interspike Interval ◽  
Interval Probability

The Combined Closed Form-Perturbation Approach to the Analysis of Mistuned Bladed Disks

1993 ◽  
Vol 115 (4) ◽  
pp. 771-780 ◽  
Author(s):  
M. P. Mignolet ◽  
C.-C. Lin
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Approximate Solutions ◽  
Forced Response ◽  
Perturbation Approach ◽  
Perturbation Techniques ◽  
Step Method ◽  
Bladed Disk

A two-step method is presented for the determination of reliable approximations of the probability density function of the forced response of a randomly mistuned bladed disk. Under the assumption of linearity, an integral representation of the probability density function of the blade amplitude is first derived. Then, deterministic perturbation techniques are employed to produce simple approximations of this function. The adequacy of the method is demonstrated by comparing several approximate solutions with simulation results.

scholarly journals Modelling of patterns and estimation of characteristic parameters

2012 ◽  
Vol 9 (1) ◽  
Author(s):  
Anamarija Borštnik Bračić ◽  
Igor Grabec ◽  
Edvard Govekar
Keyword(s):  
Probability Density Function ◽  
Production Process ◽  
Probability Density ◽  
Statistical Method ◽  
Density Function ◽  
Joint Probability ◽  
Joint Probability Density Function ◽  
Two Dimensional ◽  
Characteristic Parameters ◽  
Joint Probability Density

A two-dimensional pattern represents a fingerprint of the process that generated it. It is therefore expected that the information about the production process can be extracted from the pattern. In this paper, a non-parametric statistical method for modelling chaotic two-dimensional patterns and the estimation of the characteristic parameters is proposed. It is based on the joint probability density function of samples taken from known two-dimensional patterns representing a database. A new pattern with an unknown production process is reproduced by comparing parts of the new pattern with samples taken from the database. Because the samples in the database also include information about the production process, relevant parameters and the type of production process can be estimated simultaneously with the reproduction of patterns.

scholarly journals The Combined Closed Form–Perturbation Approach to the Analysis of Mistuned Bladed Disks

1992 ◽  
Author(s):  
Marc P. Mignolet ◽  
Chung-Chih Lin
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Approximate Solutions ◽  
Forced Response ◽  
Perturbation Approach ◽  
Perturbation Techniques ◽  
Step Method ◽  
Bladed Disk

A two-step method is presented for the determination of reliable approximations of the probability density function of the forced response of a randomly mistuned bladed disk. Under the assumption of linearity, an integral representation of the probability density function of the blade amplitude is first derived. Then, deterministic perturbation techniques are employed to produce simple approximations of this function. The adequacy of the method is demonstrated by comparing several approximate solutions with simulation results.

Probabilistic Analysis of Mistuned Bladed Disks: A Combined Closed Form-Perturbation Approach

1990 ◽  
Author(s):  
Marc P. Mignolet ◽  
Karl R. Christensen
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Approximate Solutions ◽  
Forced Response ◽  
Perturbation Approach ◽  
Perturbation Techniques ◽  
Step Method ◽  
Bladed Disk

A two-step method is presented for the determination of reliable approximations of the probability density function of the forced response of a randomly mistuned bladed disk. Under the assumption of linearity, an integral representation of the probability density function of the blade amplitude is first derived. Then, deterministic perturbation techniques are employed to produce simple approximations of this function. The adequacy of the method is assessed by comparing several approximate solutions with simulation results.

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