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Difference between revisions of "Shot effect"

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$$
 
$$
  
where  $  \dots < \tau _ {-} 1 < \tau _ {0} < \tau _ {1} < \dots < \tau _ {k} < \dots $
+
where  $  \dots < \tau _ {-1} < \tau _ {0} < \tau _ {1} < \dots < \tau _ {k} < \dots $
 
are the arrival moments of pulses, while  $  \alpha _ {k} $
 
are the arrival moments of pulses, while  $  \alpha _ {k} $
 
are random variables characterizing the magnitudes of the intensities of the pulses. In the particular case when  $  W ( t , \tau ) = W ( t - \tau ) $,  
 
are random variables characterizing the magnitudes of the intensities of the pulses. In the particular case when  $  W ( t , \tau ) = W ( t - \tau ) $,  
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$  s \leq  0 $,  
 
$  s \leq  0 $,  
 
the  $  \alpha _ {k} $
 
the  $  \alpha _ {k} $
are independent, uniformly-distributed random variables with finite variance, while  $  \dots < \tau _ {-} 1 < \tau _ {0} < \tau _ {1} < {} \dots $
+
are independent, uniformly-distributed random variables with finite variance, while  $  \dots < \tau _ {-1} < \tau _ {0} < \tau _ {1} < {} \dots $
 
forms a [[Poisson flow|Poisson flow]] of events with parameter  $  \lambda $,  
 
forms a [[Poisson flow|Poisson flow]] of events with parameter  $  \lambda $,  
 
the process  $  X ( t) $
 
the process  $  X ( t) $

Latest revision as of 09:42, 20 July 2021


A mathematical description of voltage fluctuations at the output of a linear system at the input of which there are random perturbations produced at random moments of time. If $ W ( t , \tau ) $ is the output of the system at time $ t $ resulting from a single pulse applied at time $ \tau \leq t $, the shot effect may be described by a stochastic process

$$ X ( t) = \sum _ {\{ {k } : {\tau _ {k} \leq t } \} } \alpha _ {k} W ( t , \tau _ {k} ) , $$

where $ \dots < \tau _ {-1} < \tau _ {0} < \tau _ {1} < \dots < \tau _ {k} < \dots $ are the arrival moments of pulses, while $ \alpha _ {k} $ are random variables characterizing the magnitudes of the intensities of the pulses. In the particular case when $ W ( t , \tau ) = W ( t - \tau ) $, $ W ( s) = 0 $, $ s \leq 0 $, the $ \alpha _ {k} $ are independent, uniformly-distributed random variables with finite variance, while $ \dots < \tau _ {-1} < \tau _ {0} < \tau _ {1} < {} \dots $ forms a Poisson flow of events with parameter $ \lambda $, the process $ X ( t) $ is a stationary stochastic process in the narrow sense, with

$$ {\mathsf E} X ( t) = \lambda {\mathsf E} \alpha _ {1} \int\limits _ { 0 } ^ \infty W ( s) d s , $$

$$ {\mathsf D} X ( t) = \lambda {\mathsf E} \alpha _ {1} ^ {2} \int\limits _ { 0 } ^ \infty W ^ {2} ( s) d s . $$

References

[1] J.H. Laning, R.G. Battin, "Random processes in automatic control" , McGraw-Hill (1956)

Comments

References

[a1a] S.O. Rice, "Mathematical analysis of random noise" Bell Systems Techn. J. , 23 (1944) pp. 283–332
[a1b] S.O. Rice, "Mathematical analysis of random noise" Bell Systems Techn. J. , 24 (1945) pp. 46–156
[a2] N. Wax (ed.) , Selected papers on noise and stochastic processes , Dover, reprint (1953)
[a3] E. Parzen, "Stochastic processes" , Holden-Day (1962)
[a4] E. Wong, "Stochastic processes in information and dynamical systems" , McGraw-Hill (1971)
How to Cite This Entry:
Shot effect. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Shot_effect&oldid=48691
This article was adapted from an original article by A.N. Shiryaev (originator), which appeared in Encyclopedia of Mathematics - ISBN 1402006098. See original article