Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
81
result(s) for
"Schott, René"
Sort by:
Operator calculus on graphs
This pioneering book presents a study of the interrelationships among operator calculus, graph theory, and quantum probability in a unified manner, with significant emphasis on symbolic computations and an eye toward applications in computer science.
eBook
Dynamic random walks : theory and applications
The aim of this book is to report on the progress realized in probability theory in the field of dynamic random walks and to present applications in computer science, mathematical physics and finance.Each chapter contains didactical material as well as more advanced technical sections.
eBook
Integration with respect to the non-commutative fractional Brownian motion
We study the issue of integration with respect to the non-commutative fractional Brownian motion, that is the analog of the standard fractional Brownian motion in a non-commutative probability setting.
When the Hurst index H of the process is stricly larger than 1/2, integration can be handled through the so-called Young procedure. The situation where H = 1/2 corresponds to the specific free case, for which an Itô-type approach is known to be possible.
When H < 1/2, rough-path-type techniques must come into the picture, which, from a theoretical point of view, involves the use of some a-priori-defined Lévy area process. We show that such an object can indeed be “canonically” constructed for any
H
∈
(
1
4
,
1
2
)
. Finally, when H ≤ 1/4, we exhibit a similar nonconvergence phenomenon as for the non-diagonal entries of the (classical) Lévy area above the standard fractional Brownian motion.
Journal Article
Krawtchouk transforms and convolutions
We present an operator calculus based on Krawtchouk polynomials, including Krawtchouk transforms and corresponding convolution structure which provides an inherently discrete alternative to Fourier analysis. This approach is well suited for applications such as digital image processing. This paper includes the theoretical aspects and some basic examples.
Journal Article
Information Transmission under Random Emission Constraints
We model the transmission of a message on the complete graph with n vertices and limited resources. The vertices of the graph represent servers that may broadcast the message at random. Each server has a random emission capital that decreases at each emission. Quantities of interest are the number of servers that receive the information before the capital of all the informed servers is exhausted and the exhaustion time. We establish limit theorems (law of large numbers, central limit theorem and large deviation principle), as n → ∞, for the proportion of informed vertices before exhaustion and for the total duration. The analysis relies on a construction of the transmission procedure as a dynamical selection of successful nodes in a Galton–Watson tree with respect to the success epochs of the coupon collector problem.
Journal Article
Real-time Computation of a Patient's Respiratory Effort During Ventilation
In this paper, a new algorithm is proposed to compute the spontaneously generated respiratory effort during ventilation.
The algorithm computes a ventilated patient's respiratory effort in real-time by analyzing the respiratory pressure and flow signals that are acquired from the ventilator. The method requires an initial period where the patient's respiratory muscles are fully relaxed, for example during or shortly after surgery. During this period the patient's inspiratory airway resistance R(in), the expiratory airway resistance R(ex), the lung-thorax compliance C(lt) and the residual pressure after an infinitely long expiration P(0) are estimated by fitting the measured flow onto the measured pressure at the mouth using a model of the patient's respiratory system. When the patient starts breathing, the relation between the measured pressure and the flow changes, from which the respiratory effort of the patient P(mus) can be computed.
The pressure P(mus) can be computed in real-time by using an equivalent model of the respiratory system of the patient. The estimation can be done with a recursive least squares (RLS) method. Further, the resulting P(mus) signal appears to have a constant shape, in which the main changing factor is the maximum amplitude per breath.
The respiratory effort increases over time until the patient is disconnected from the ventilator. We hope the maximum amplitude can be used as an indicator of the pressure the muscles of the patient are able to produce. This amplitude of the (mus)-signal in combination with the standard deviation (SD) may eventually lead to a new indicator to determine the moment that the patient can be weaned from the ventilator. This will have to be examined in the future.
Journal Article
Hybrid PSO-SA Type Algorithms for Multimodal Function Optimization and Reducing Energy Consumption in Embedded Systems
The paper presents a novel hybrid evolutionary algorithm that combines Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithms. When a local optimal solution is reached with PSO, all particles gather around it, and escaping from this local optima becomes difficult. To avoid premature convergence of PSO, we present a new hybrid evolutionary algorithm, called HPSO-SA, based on the idea that PSO ensures fast convergence, while SA brings the search out of local optima because of its strong local-search ability. The proposed HPSO-SA algorithm is validated on ten standard benchmark multimodal functions for which we obtained significant improvements. The results are compared with these obtained by existing hybrid PSO-SA algorithms. In this paper, we provide also two versions of HPSO-SA (sequential and distributed) for minimizing the energy consumption in embedded systems memories. The two versions, of HPSO-SA, reduce the energy consumption in memories from 76% up to 98% as compared to Tabu Search (TS). Moreover, the distributed version of HPSO-SA provides execution time saving of about 73% up to 84% on a cluster of 4 PCs.
Journal Article
Large Deviations Analysis for Distributed Algorithms in an Ergodic Markovian Environment
We provide a large deviations analysis of deadlock phenomena occurring in distributed systems sharing common resources. In our model transition probabilities of resource allocation and deallocation are time and space dependent. The process is driven by an ergodic Markov chain and is reflected on the boundary of the
d
-dimensional cube. In the large resource limit, we prove Freidlin-Wentzell estimates, we study the asymptotic of the deadlock time and we show that the quasi-potential is a viscosity solution of a Hamilton-Jacobi equation with a Neumann boundary condition. We give a complete analysis of the colliding 2-stacks problem and show an example where the system has a stable attractor which is a limit cycle.
Journal Article