Search results for "Stochastic optimization"
showing 8 items of 38 documents
Stochastic Control Problems
2003
The general theory of stochastic processes originated in the fundamental works of A. N. Kolmogorov and A. Ya. Khincin at the beginning of the 1930s. Kolmogorov, 1938 gave a systematic and rigorous construction of the theory of stochastic processes without aftereffects or, as it is customary to say nowadays, Markov processes. In a number of works, Khincin created the principles of the theory of so-called stationary processes.
Registration and fusion of segmented left atrium CT images with CARTO electrical maps for the ablative treatment of atrial fibrillation
2005
This study aims to extract the interior surface of the left atrium (LA) and pulmonary veins (PVs) from threedimensional tomographic data and to integrate it with LA CARTO electrical maps. The separation of LA and PVs from other overlapping structures of the heart was performed processing 3D CT data by marker-controlled watershed segmentation and surface extraction. CARTO maps were then registered on the L A internal surface by a stochastic optimization algorithm based on simulated annealing. The residual registration error resulted inferior to 3 mm. The integration between electrophysiological and high resolved anatomic information of LA results feasible and may constitute a significant sup…
HOW SMART DOES AN AGENT NEED TO BE?
2005
The classic distributed computation is done by atoms, molecules or spins in vast numbers, each equipped with nothing more than the knowledge of their immediate neighborhood and the rules of statistical mechanics. These agents, 1023 or more, are able to form liquids and solids from gases, realize extremely complex ordered states, such as liquid crystals, and even decode encrypted messages. We will describe a study done for a sensor-array "challenge problem" in which we have based our approach on old-fashioned simulated annealing to accomplish target acquisition and tracking under the rules of statistical mechanics. We believe the many additional constraints that occur in the real problem ca…
Network Slicing Enabled Resource Management for Service-Oriented Ultra-Reliable and Low-Latency Vehicular Networks
2020
Network slicing has been considered as a promising candidate to provide customized services for vehicular applications that have extremely high requirements of latency and reliability. However, the high mobility of vehicles poses significant challenges to resource management in such a stochastic vehicular environment with time-varying service demands. In this paper, we develop an online network slicing scheduling strategy for joint resource block (RB) allocation and power control in vehicular networks. The long-term time-averaged total system capacity is maximized while guaranteeing strict ultra-reliable and low-latency requirements of vehicle communication links, subject to stability const…
Feature selection: A multi-objective stochastic optimization approach
2020
The feature subset task can be cast as a multiobjective discrete optimization problem. In this work, we study the search algorithm component of a feature subset selection method. We propose an algorithm based on the threshold accepting method, extended to the multi-objective framework by an appropriate definition of the acceptance rule. The method is used in the task of identifying relevant subsets of features in a Web bot recognition problem, where automated software agents on the Web are identified by analyzing the stream of HTTP requests to a Web server.
Solving chance constrained optimal control problems in aerospace via Kernel Density Estimation
2017
International audience; The goal of this paper is to show how non-parametric statistics can be used to solve some chance constrained optimization and optimal control problems. We use the Kernel Density Estimation method to approximate the probability density function of a random variable with unknown distribution , from a relatively small sample. We then show how this technique can be applied and implemented for a class of problems including the God-dard problem and the trajectory optimization of an Ariane 5-like launcher.
Recursion at the crossroads of sequence modeling, random trees, stochastic algorithms and martingales
2013
This monograph synthesizes several studies spanning from dynamical systems in the statistical analysis of sequences, to analysis of algorithms in random trees and discrete stochastic processes. These works find applications in various fields ranging from biological sequences to linear regression models, branching processes, through functional statistics and estimates of risk indicators for insurances. All the established results use, in one way or another, the recursive property of the structure under study, by highlighting invariants such as martingales, which are at the heart of this monograph, as tools as well as objects of study.
Simultaneous optimization of harvest schedule and measurement strategy
2013
In many recent studies, the value of forest inventory information in the harvest scheduling has been examined. Usually only the profitability of measuring simultaneously all the stands in the area is examined. Yet, it may be more profitable to concentrate the measurement efforts to some subset of them. In this paper, the authors demonstrate that stochastic optimization can be used for defining the optimal measurement strategy simultaneously with the harvest decisions. The results show that without end-inventory constraints, it was most profitable to measure the stands that were just below the medium age. Measuring the oldest stands was not profitable at all. It turned out to be profitable t…