659 research outputs found

    Cross-coupled doa trackers

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    A new robust, low complexity algorithm for multiuser tracking is proposed, modifying the two-stage parallel architecture of the estimate-maximize (EM) algorithm. The algorithm copes with spatially colored noise, large differences in source powers, multipath, and crossing trajectories. Following a discussion on stability, the simulations demonstrate an asymptotic and tracking behavior that neither the EM nor a nonparallelized tracker can emulate.Peer ReviewedPostprint (published version

    Variance and interest rate risk in unit-linked insurance policies

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    One of the risks derived from selling long term policies that any insurance company has, arises from interest rates. In this paper we consider a general class of stochastic volatility models written in forward variance form. We also deal with stochastic interest rates to obtain the risk-free price for unit-linked life insurance contracts, as well as providing a perfect hedging strategy by completing the market. We conclude with a simulation experiment, where we price unit-linked policies using Norwegian mortality rates. In addition we compare prices for the classical Black-Scholes model against the Heston stochastic volatility model with a Vasicek interest rate model.Comment: 21 pages, 7 figure

    Model Design of Wind/PV/Fossil-Fuel Hybrid Systems

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    This paper presents the analysis and design of a mathematical model for a hybrid-power generation system consisting of a photovoltaic array, wind-turbines, a batterybank and a backup fossil-fuel generator. The static mathematical models of each element are validated by comparing them with field-data obtained in an experimental hybrid generation system in Pachuca, Mexico. Two different state-of-charge models were simulated and compared. The results are presented in this paper. The main purpose of this work is the development of a fuzzy-supervisory-controller for small hybrid-systems

    An adaptive design of an all-zero spectral estimator

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    AplicaciĂłn del muestreo enfatizado a la evaluaciĂłn de transmisiones digitales

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    The Importance Sampling Technique is a method for reducing the computational effort in Montecarlo simulations for obtaining the relative frequency of an event having a very low probability. While this method is well known in general Operations Research /1//2//3/ and Radar /4//5//6//7//8//9//10/, it has not been considered in digital communication problems. This paper aims to introduce the Importance Sampling concept in this communication context.Peer ReviewedPostprint (published version
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