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Economic assessment of the Champagne wine qualitative stock mecanism

Jacques Laye, Maximilien Laye (2006)

RAIRO - Operations Research

In the wine AOC system, the regulation of quantities performed by the professional organizations is aimed to smooth the variations of the quality of the wine due to the variations in the climate that affect the quality of the grapes. Nevertheless, this regulation could be damaging to the consumers due to the price increase resulting from the reduction of the quantities sold on the market. We propose a stochastic control model and a simulation tool able to measure the effects of this mechanism...

Efficient measurement of higher-order statistics of stochastic processes

Wladyslaw Magiera, Urszula Libal, Agnieszka Wielgus (2018)

Kybernetika

This paper is devoted to analysis of block multi-indexed higher-order covariance matrices, which can be used for the least-squares estimation problem. The formulation of linear and nonlinear least squares estimation problems is proposed, showing that their statements and solutions lead to generalized `normal equations', employing covariance matrices of the underlying processes. Then, we provide a class of efficient algorithms to estimate higher-order statistics (generalized multi-indexed covariance...

Efficient RGB-D data processing for feature-based self-localization of mobile robots

Marek Kraft, Michał Nowicki, Rudi Penne, Adam Schmidt, Piotr Skrzypczyński (2016)

International Journal of Applied Mathematics and Computer Science

The problem of position and orientation estimation for an active vision sensor that moves with respect to the full six degrees of freedom is considered. The proposed approach is based on point features extracted from RGB-D data. This work focuses on efficient point feature extraction algorithms and on methods for the management of a set of features in a single RGB-D data frame. While the fast, RGB-D-based visual odometry system described in this paper builds upon our previous results as to the general...

Eigenspace of a three-dimensional max-Łukasiewicz fuzzy matrix

Imran Rashid, Martin Gavalec, Sergeĭ Sergeev (2012)

Kybernetika

Eigenvectors of a fuzzy matrix correspond to stable states of a complex discrete-events system, characterized by a given transition matrix and fuzzy state vectors. Description of the eigenspace (set of all eigenvectors) for matrices in max-min or max-drast fuzzy algebra was presented in previous papers. In this paper the eigenspace of a three-dimensional fuzzy matrix in max-Łukasiewicz algebra is investigated. Necessary and sufficient conditions are shown under which the eigenspace restricted to...

Employing different loss functions for the classification of images via supervised learning

Radu Boţ, André Heinrich, Gert Wanka (2014)

Open Mathematics

Supervised learning methods are powerful techniques to learn a function from a given set of labeled data, the so-called training data. In this paper the support vector machines approach is applied to an image classification task. Starting with the corresponding Tikhonov regularization problem, reformulated as a convex optimization problem, we introduce a conjugate dual problem to it and prove that, whenever strong duality holds, the function to be learned can be expressed via the dual optimal solutions....

Entropic Conditions and Hedging

Samuel Njoh (2007)

ESAIM: Probability and Statistics

In many markets, especially in energy markets, electricity markets for instance, the detention of the physical asset is quite difficult. This is also the case for crude oil as treated by Davis (2000). So one can identify a good proxy which is an asset (financial or physical) (one)whose the spot price is significantly correlated with the spot price of the underlying (e.g. electicity or crude oil). Generally, the market could become incomplete. We explicit exact hedging strategies for exponential...

Epoch-incremental reinforcement learning algorithms

Roman Zajdel (2013)

International Journal of Applied Mathematics and Computer Science

In this article, a new class of the epoch-incremental reinforcement learning algorithm is proposed. In the incremental mode, the fundamental TD(0) or TD(λ) algorithm is performed and an environment model is created. In the epoch mode, on the basis of the environment model, the distances of past-active states to the terminal state are computed. These distances and the reinforcement terminal state signal are used to improve the agent policy.

Equivalent cost functionals and stochastic linear quadratic optimal control problems

Zhiyong Yu (2013)

ESAIM: Control, Optimisation and Calculus of Variations

This paper is concerned with the stochastic linear quadratic optimal control problems (LQ problems, for short) for which the coefficients are allowed to be random and the cost functionals are allowed to have negative weights on the square of control variables. We propose a new method, the equivalent cost functional method, to deal with the LQ problems. Comparing to the classical methods, the new method is simple, flexible and non-abstract. The new method can also be applied to deal with nonlinear...

Ergodic control of linear stochastic equations in a Hilbert space with fractional Brownian motion

Tyrone E. Duncan, B. Maslowski, B. Pasik-Duncan (2015)

Banach Center Publications

A linear-quadratic control problem with an infinite time horizon for some infinite dimensional controlled stochastic differential equations driven by a fractional Brownian motion is formulated and solved. The feedback form of the optimal control and the optimal cost are given explicitly. The optimal control is the sum of the well known linear feedback control for the associated infinite dimensional deterministic linear-quadratic control problem and a suitable prediction of the adjoint optimal system...

Estimació del pol i de la variància del soroll d'un model AR (1) mitjançant filtratge no lineal.

M.ª Pilar Muñoz Gracia, Juan José Egozcue Rubí, Manuel Martí Recobert (1988)

Qüestiió

La estimación de los parámetros asociados a un proceso ARMA puede plantearse como un problema de filtrado no lineal. Para determinar un estimador recursivo de estos parámetros se define un vector de estado ampliado que incluye las variables de estado y los parámetros a estimar. Con un enfoque bayesiano se determina la distribución a posteriori del vector de estado ampliado. La síntesis del filtro no lineal permite: i) estimar los parámetros y determinar su precisión para un tamaño de muestra dado,...

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