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An explicit solution for optimal investment problems with autoregressive prices and exponential utility

Sándor Deák, Miklós Rásonyi (2015)

Applicationes Mathematicae

We calculate explicitly the optimal strategy for an investor with exponential utility function when the price of a single risky asset (stock) follows a discrete-time autoregressive Gaussian process. We also calculate its performance and analyse it when the trading horizon tends to infinity. Dependence of the asymptotic performance on the autoregression parameter is determined. This provides, to the best of our knowledge, the first instance of a theorem linking directly the memory of the asset price...

An optimality system for finite average Markov decision chains under risk-aversion

Alfredo Alanís-Durán, Rolando Cavazos-Cadena (2012)

Kybernetika

This work concerns controlled Markov chains with finite state space and compact action sets. The decision maker is risk-averse with constant risk-sensitivity, and the performance of a control policy is measured by the long-run average cost criterion. Under standard continuity-compactness conditions, it is shown that the (possibly non-constant) optimal value function is characterized by a system of optimality equations which allows to obtain an optimal stationary policy. Also, it is shown that the...

An SFDI observer-based scheme for a general aviation aircraft

Marco Ariola, Massimiliano Mattei, Immacolata Notaro, Federico Corraro, Adolfo Sollazzo (2015)

International Journal of Applied Mathematics and Computer Science

The problem of detecting and isolating sensor faults (sensor fault detection and isolation-SFDI) on a general aviation aircraft, in the presence of external disturbances, is considered. The proposed approach consists of an extended Kalman observer applied to an augmented aircraft plant, where some integrators are added to the output variables subject to faults. The output of the integrators should be ideally zero in the absence of model uncertainties, external disturbances and sensor faults. A threshold-based...

An unbounded Berge's minimum theorem with applications to discounted Markov decision processes

Raúl Montes-de-Oca, Enrique Lemus-Rodríguez (2012)

Kybernetika

This paper deals with a certain class of unbounded optimization problems. The optimization problems taken into account depend on a parameter. Firstly, there are established conditions which permit to guarantee the continuity with respect to the parameter of the minimum of the optimization problems under consideration, and the upper semicontinuity of the multifunction which applies each parameter into its set of minimizers. Besides, with the additional condition of uniqueness of the minimizer, its...

An unscented Kalman filter in designing dynamic GMDH neural networks for robust fault detection

Marcin Mrugalski (2013)

International Journal of Applied Mathematics and Computer Science

This paper presents an identification method of dynamic systems based on a group method of data handling approach. In particular, a new structure of the dynamic multi-input multi-output neuron in a state-space representation is proposed. Moreover, a new training algorithm of the neural network based on the unscented Kalman filter is presented. The final part of the work contains an illustrative example regarding the application of the proposed approach to robust fault detection of a tunnel furnace....

Another set of verifiable conditions for average Markov decision processes with Borel spaces

Xiaolong Zou, Xianping Guo (2015)

Kybernetika

In this paper we give a new set of verifiable conditions for the existence of average optimal stationary policies in discrete-time Markov decision processes with Borel spaces and unbounded reward/cost functions. More precisely, we provide another set of conditions, which only consists of a Lyapunov-type condition and the common continuity-compactness conditions. These conditions are imposed on the primitive data of the model of Markov decision processes and thus easy to verify. We also give two...

Application of triple correlation and bispectrum for interference immunity improvement in telecommunications systems

Pavel Molchanov, Alexandr Totsky (2008)

International Journal of Applied Mathematics and Computer Science

This paper presents a new noise immunity encoding/decoding technique by using the features of triple correlation and bispectrum widely employed in digital signal processing systems operating in noise environments. The triple correlationand bispectrum-based encoding/decoding algorithm is tested for a digital radio telecommunications binary frequency shift keying system. The errorless decoding probability was analyzed by means of computer simulation for the transmission and reception of a test message...

Applications of regime-switching models based on aggregation operators

Jozef Komorník, Magda Komorníková (2007)

Kybernetika

A synthesis of recent development of regime-switching models based on aggregation operators is presented. It comprises procedures for model specification and identification, parameter estimation and model adequacy testing. Constructions of models for real life data from hydrology and finance are presented.

Approximation and estimation in Markov control processes under a discounted criterion

J. Adolfo Minjárez-Sosa (2004)

Kybernetika

We consider a class of discrete-time Markov control processes with Borel state and action spaces, and k -valued i.i.d. disturbances with unknown density ρ . Supposing possibly unbounded costs, we combine suitable density estimation methods of ρ with approximation procedures of the optimal cost function, to show the existence of a sequence { f ^ t } of minimizers converging to an optimal stationary policy f .

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