Difference between revisions of "Shot effect"
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$$ | $$ | ||
− | where $ \dots < \tau _ {-} | + | 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 _ {-} | + | 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) |
Shot effect. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Shot_effect&oldid=48691