Equations for stochastic path integrals

Author(s):  
M. S. Bartlett

Apart from the study of the integralwhere {X(u)} is a stationary Gaussian process with autocorrelation function ρ(t), by Kac and Siegert(1), most stochastic functionals of the general typehave been considered for {X(u)} either additive or Markovian (see, for example, (2), (3)), and in the Markovian case only for diffusion-type processes (Darling and Siegert (4)). More general approaches exist (e.g. (5), (6)), but seem less concerned with the investigation of specific problems. Some preliminary remarks here are therefore aimed at examining the structure of integrals of type (2), or such further extensions of the formal Riemann sum typethat would be expected to have well-behaved distributional properties for {X(t)} Markovian, and associated equations for studying these properties. As an example, the sumsay, is considered (i) for the normal linear Markovian process, (ii) for simple birth-and-death and emigration—immigration processes.

Author(s):  
Fariba Salehi ◽  
Mohammad Reza Keyvanpour ◽  
Arash Sharifi

2019 ◽  
Vol 41 (10) ◽  
pp. 2886-2896 ◽  
Author(s):  
Yang Chen ◽  
Dazhi Wang

Much more attention has been focused on studying and applying general type-2 fuzzy logic systems (GT2 FLSs) in recent years. The paper designs a type of Mamdani GT2 FLS for studying forecasting problems based on the data of permanent magnetic drive (PMD) loss. During the system design process, we choose the primary membership functions (MFs) of antecedent, consequent and input measurement general type-2 fuzzy sets (GT2 FSs) as Gaussian type MFs with uncertain standard deviations. The corresponding vertical slices (secondary MFs) are chosen as the triangle MFs. All the parameters of Mamdani GT2 FLSs are optimized by the quantum particle swarm optimization (QPSO) algorithms. Noisy data of PMD loss are adopted for both training and testing the proposed FLSs forecasting approaches. Simulation studies and convergence analysis are employed to show the effectiveness and feasibility of the proposed GT2 FLSs forecasting methods compared with their T1 and IT2 counterparts.


1980 ◽  
Vol 17 (04) ◽  
pp. 1117-1120 ◽  
Author(s):  
L. Valadares Tavares

A new markovian process {X i : i = 0, 1, 2, ·· ·} following a negative exponential distribution and with the same autocorrelation function as the lag-1 autoregressive process is proposed and studied in this paper. The exact distribution of the maxima and of the minima of n consecutive Xi values are obtained and the exact expected upcrossing interval is given for any crossing level.


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