scholarly journals A Higher Order Uniform Convergence Result for a Turning Point Problem

1993 ◽  
Vol 12 (4) ◽  
pp. 723-728 ◽  
Author(s):  
H.-G. Roos ◽  
R. Vulanović
Keyword(s):  
Uniform Convergence ◽  
Turning Point ◽  
Convergence Result ◽  
Higher Order ◽  
Point Problem

Three turning-point problem

1973 ◽  
Vol 6 (11) ◽  
pp. 423-426 ◽  
Author(s):  
S. S. Wald ◽  
P. Lu
Keyword(s):  
Turning Point ◽  
Point Problem

scholarly journals Two-Point Problem for Higher-Order Systems

2001 ◽  
Vol 253 (1) ◽  
pp. 243-249 ◽  
Author(s):  
Paolo Cubiotti ◽  
Beatrice Di Bella
Keyword(s):  
Higher Order ◽  
Point Problem

scholarly journals Iterative Algorithms for the Split Problem and Its Convergence Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Zhangsong Yao ◽  
Arif Rafiq ◽  
Shin Min Kang ◽  
Li-Jun Zhu
Keyword(s):  
Fixed Point ◽  
Common Fixed Point ◽  
Iterative Algorithms ◽  
Split Feasibility Problem ◽  
Fixed Point Problem ◽  
Convergence Result ◽  
Feasibility Problem ◽  
Point Problem ◽  
Common Fixed Point Problem ◽  
Split Common Fixed Point

Now, it is known that the split common fixed point problem is a generalization of the split feasibility problem and of the convex feasibility problem. In this paper, the split common fixed point problem associated with the pseudocontractions is studied. An iterative algorithm has been presented for solving the split common fixed point problem. Strong convergence result is obtained.

A uniform convergence theorem for the numerical solving of the nonlinear filtering problem

1998 ◽  
Vol 35 (04) ◽  
pp. 873-884 ◽  
Author(s):  
P. Del Moral
Keyword(s):  
Monte Carlo ◽  
Uniform Convergence ◽  
Convergence Theorem ◽  
Nonlinear Filtering ◽  
Partial Information ◽  
Particle System ◽  
Convergence Result ◽  
Recursive Solution ◽  
Ergodic Condition ◽  
Filtering Problem

The filtering problem concerns the estimation of a stochastic process X from its noisy partial information Y. With the notable exception of the linear-Gaussian situation, general optimal filters have no finitely recursive solution. The aim of this work is the design of a Monte Carlo particle system approach to solve discrete time and nonlinear filtering problems. The main result is a uniform convergence theorem. We introduce a concept of regularity and we give a simple ergodic condition on the signal semigroup for the Monte Carlo particle filter to converge in law and uniformly with respect to time to the optimal filter, yielding what seems to be the first uniform convergence result for a particle approximation of the nonlinear filtering equation.

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