Search results for "ESTIMATOR"
showing 10 items of 313 documents
Combining Defocus and Photoconsistency for Depth Map Estimation in 3D Integral Imaging
2017
This paper presents the application of a depth estimation method for scenes acquired using a Synthetic Aperture Integral Imaging (SAII) technique. SAII is an autostereoscopic technique consisting of an array of cameras that acquires images from different perspectives. The depth estimation method combines a defocus and a correspondence measure. This approach obtains consistent results and shows noticeable improvement in the depth estimation as compared to a minimum variance minimisation strategy, also tested in our scenes. Further improvements are obtained for both methods when they are fed into a regularisation approach that takes into account the depth in the spatial neighbourhood of a pix…
The Hierarchical Continuous Pursuit Learning Automation: A Novel Scheme for Environments With Large Numbers of Actions.
2019
Although the field of learning automata (LA) has made significant progress in the past four decades, the LA-based methods to tackle problems involving environments with a large number of actions is, in reality, relatively unresolved. The extension of the traditional LA to problems within this domain cannot be easily established when the number of actions is very large. This is because the dimensionality of the action probability vector is correspondingly large, and so, most components of the vector will soon have values that are smaller than the machine accuracy permits, implying that they will never be chosen . This paper presents a solution that extends the continuous pursuit paradigm to …
The Hierarchical Continuous Pursuit Learning Automation for Large Numbers of Actions
2018
Part 10: Learning - Intelligence; International audience; Although the field of Learning Automata (LA) has made significant progress in the last four decades, the LA-based methods to tackle problems involving environments with a large number of actions are, in reality, relatively unresolved. The extension of the traditional LA (fixed structure, variable structure, discretized, and pursuit) to problems within this domain cannot be easily established when the number of actions is very large. This is because the dimensionality of the action probability vector is correspondingly large, and consequently, most components of the vector will, after a relatively short time, have values that are smal…
SAVU: A Statistical Approach for Uncertain Data in Dynamics of Axially Moving Materials
2012
In physics and engineering problems, model input is never exact. The effect of small uncertainties on the solution is thus an important question. In this study, a direct statistical-visual approach to approximate the solution set is investigated in the context of axially moving materials. The multidimensional probability distribution for the input uncertainties is assumed known. It is considered as a deterministic object, which is then mapped through the model. The resulting probability density of the model output is visualized. The proposed system consists of three non-trivial parts, which are briefly discussed: a multidimensional sampler, a density estimator, and a high dynamic range (HDR…
Food predictability determines space use of endangered vultures: implications for management of supplementary feeding.
2013
Understanding space use of free-living endangered animals is key to inform management decisions for conservation planning. Like most scavengers, vultures have evolved under a context of unpredictability of food resources (i.e. exploiting scattered carcasses that are intermittently available). However, the role of predictable sources of food in shaping spatial ecology of vultures has seldom been studied in detail. Here, we quantify the home range of the Egyptian vulture (Neophron percnopterus), a long-lived raptor which has experienced severe population decline throughout its range and is qualified as endangered worldwide. To this end six adults were tracked by satellite telemetry in Spain d…
Generalized Bayesian pursuit: A novel scheme for multi-armed Bernoulli bandit problems
2011
Published version of a chapter in the book: IFIP Advances in Information and Communication Technology. Also available from the publisher at: http;//dx.doi.org/10.1007/978-3-642-23960-1_16 In the last decades, a myriad of approaches to the multi-armed bandit problem have appeared in several different fields. The current top performing algorithms from the field of Learning Automata reside in the Pursuit family, while UCB-Tuned and the ε -greedy class of algorithms can be seen as state-of-the-art regret minimizing algorithms. Recently, however, the Bayesian Learning Automaton (BLA) outperformed all of these, and other schemes, in a wide range of experiments. Although seemingly incompatible, in…
On the Correlation and Ergodic Properties of the Squared Envelope of SOC Rayleigh Fading Channel Simulators
2012
Published version of an article in the journal: Wireless Personal Communications. Also available from the publisher at: http://dx.doi.org/10.1007/s11277-011-0493-2 In this paper, we investigate the correlation and ergodic properties of the squared envelope of a class of autocorrelation-ergodic (AE) sum-of-cisoids (SOC) simulation models for mobile Rayleigh fading channels. Novel closed-form expressions are presented for both the ensemble and the time autocorrelation functions (ACFs) of the SOC simulation model’s squared envelope. These expressions have been derived by assuming that the SOC model’s inphase and quadrature (IQ) components have arbitrary autocorrelation and cross-correlation pr…
Tracking the Preferences of Users Using Weak Estimators
2011
Published version of am article from the book:AI 2011: Advances in Artificial Intelligence. Also available from the publisher on SpringerLink:http://dx.doi.org/10.1007/978-3-642-25832-9_81 Since a social network, by definition, is so diverse, the problem of estimating the preferences of its users is becoming increasingly essential for personalized applications which range from service recommender systems to the targeted advertising of services. However, unlike traditional estimation problems where the underlying target distribution is stationary, estimating a user’s interests, typically, involves non-stationary distributions. The consequent time varying nature of the distribution to be trac…
A Spatial Difference-in-Differences Estimator to Evaluate the Effect of Change in Public Mass Transit Systems on House Prices
2014
Evaluating the impact of public mass transit systems on real-estate values is an important application of the hedonic price model (HPM). Recently, a mathematical transformation of this approach has been proposed to account for the potential omission of latent spatial variables that may overestimate the impact of accessibility to mass transit systems on values. The development of a Difference-in-Differences (DID) estimator, based on the repeat-sales approach, is a move in the right direction. However, such an estimator neglects the possibility that specification of the price equation may follow a spatial autoregressive process with respect to the dependent variable. The objective of this pap…
Evaluation of models for estimating solar irradiation on vertical surfaces at Valencia, Spain
1991
Abstract Hourly irradiation data recorded on vertical surfaces at north, east, south, and west orientations during the winter period going from December 1989 to March 1990 in Valencia, Spain, have been compared with estimated solar irradiation from several tilted-surface models. The isotropic-, Temps' and Coulson's-, Klucher's-, Hay's-, Skartveit's and Olseth's-, Gueymard's- and Perez' (simplified) models have been considered for this comparison. Root-mean-square-difference (RMSD), mean-bias-difference (MBD) and mean-absolute-difference (MAD) estimators have been used to measure the departure of models from experimental data. Modeled values are evaluated with the original coefficients propo…