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We investigate the almost sure asymptotic properties of vector martingale transforms. Assuming some appropriate regularity conditions both on the increasing process and on the moments of the martingale, we prove that normalized moments of…

Probability · Mathematics 2018-12-05 Bernard Bercu , Peggy Cénac , Guy Fayolle

In this paper we survey the almost sure central limit theorem and its functional form (quenched) for stationary and ergodic processes. For additive functionals of a stationary and ergodic Markov chain these theorems are known under the…

Probability · Mathematics 2013-04-17 Magda Peligrad

We develop a general approach of the almost sure central limit theorem for the quasi-continuous vectorial martingales and we release a quadratic extension of this theorem while specifying speeds of convergence. As an application of this…

Probability · Mathematics 2014-08-06 Faouzi Chaabane , Ahmed Kebaier

In this paper we estimate the rest of the approximation of a stationary process by a martingale in terms of the projections of partial sums. Then, based on this estimate, we obtain almost sure approximation of partial sums by a martingale…

Probability · Mathematics 2011-05-05 Florence Merlevède , Costel Peligrad , Magda Peligrad

The usefulness of persistent excitation is well-known in the control community. Thanks to a persistently excited adaptive tracking control, we show that it is possible to avoid the strong controllability assumption recently proposed in the…

Probability · Mathematics 2009-03-17 Bernard Bercu , Victor Vazquez

This paper presents some limit theorems for certain functionals of moving averages of semimartingales plus noise which are observed at high frequency. Our method generalizes the pre-averaging approach (see [Bernoulli 15 (2009) 634--658,…

Statistics Theory · Mathematics 2010-10-05 Jean Jacod , Mark Podolskij , Mathias Vetter

In this paper we study the almost sure conditional central limit theorem in its functional form for a class of random variables satisfying a projective criterion. Applications to strongly mixing processes and non irreducible Markov chains…

Probability · Mathematics 2013-03-07 Jérôme Dedecker , Florence Merlevède , Magda Peligrad

In this paper, we develop necessary and sufficient conditions for the validity of a martingale approximation for the partial sums of a stationary process in terms of the maximum of consecutive errors. Such an approximation is useful for…

Probability · Mathematics 2011-02-11 Mikhail Gordin , Magda Peligrad

We propose a new concept of strong controllability associated with the Schur complement of a suitable limiting matrix. This concept allows us to extend the previous results associated with multidimensional ARX models. On the one hand, we…

Probability · Mathematics 2008-01-22 Bernard Bercu , Victor Vazquez

This work is devoted to the almost sure stabilization of adaptive control systems that involve an unknown Markov chain. The control system displays continuous dynamics represented by differential equations and discrete events given by a…

Probability · Mathematics 2008-07-10 Bernard Bercu , Francois Dufour , G. George Yin

In this paper, we establish an almost sure central limit theorem for a general random sequence under a strong approximation condition. Additionally, we derive the law of the iterated logarithm for the center of mass corresponding to a…

Probability · Mathematics 2024-07-08 Zhishui Hua , Wei Wanga , Liang Dong

In this paper we study the almost sure central limit theorem started from a point for additive functionals of a stationary and ergodic Markov chain via a martingale approximation in the almost sure sense. As a consequence we derive the…

Probability · Mathematics 2009-11-26 Christophe Cuny , Magda Peligrad

This paper considers real-time control and learning problems for finite-dimensional linear systems under binary-valued and randomly disturbed output observations. This has long been regarded as an open problem because the exact values of…

Systems and Control · Electrical Eng. & Systems 2024-11-12 Lantian Zhang , Lei Guo

We study the almost-sure termination problem for probabilistic programs. First, we show that supermartingales with lower bounds on conditional absolute difference provide a sound approach for the almost-sure termination problem. Moreover,…

Logic in Computer Science · Computer Science 2018-08-24 Mingzhang Huang , Hongfei Fu , Krishnendu Chatterjee

This paper aims first at a simultaneous axiomatic presentation of the proof of optimal convergence rates for adaptive finite element methods and second at some refinements of particular questions like the avoidance of (discrete) lower…

Numerical Analysis · Mathematics 2014-03-14 Carsten Carstensen , Michael Feischl , Marcus Page , Dirk Praetorius

We establish the central limit theorem for linear processes with dependent innovations including martingales and mixingale type of assumptions as defined in McLeish [Ann. Probab. 5 (1977) 616--621] and motivated by Gordin [Soviet Math.…

Probability · Mathematics 2007-05-23 Magda Peligrad , Sergey Utev

In this paper we survey and further study partial sums of a stationary process via approximation with a martingale with stationary differences. Such an approximation is useful for transferring from the martingale to the original process the…

Probability · Mathematics 2011-05-24 Magda Peligrad

We consider a random walk on $\R^d$ in a polynomially mixing random environment that is refreshed at each time step. We use a martingale approach to give a necessary and sufficient condition for the almost-sure functional central limit…

Probability · Mathematics 2010-12-14 Mathew Joseph , Firas Rassoul-Agha

We develop a martingale approximation approach to studying the limiting behavior of quadratic forms of Markov chains. We use the technique to examine the asymptotic behavior of lag-window estimators in time series and we apply the results…

Probability · Mathematics 2011-08-16 Yves F. Atchade , Matias D. Cattaneo

This paper proposes a framework for adaptively learning a feedback linearization-based tracking controller for an unknown system using discrete-time model-free policy-gradient parameter update rules. The primary advantage of the scheme over…

Machine Learning · Computer Science 2020-04-07 Tyler Westenbroek , Eric Mazumdar , David Fridovich-Keil , Valmik Prabhu , Claire J. Tomlin , S. Shankar Sastry
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