44 resultados para Bayesian frameworks


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The minimum cost classifier when general cost functionsare associated with the tasks of feature measurement and classification is formulated as a decision graph which does not reject class labels at intermediate stages. Noting its complexities, a heuristic procedure to simplify this scheme to a binary decision tree is presented. The optimizationof the binary tree in this context is carried out using ynamicprogramming. This technique is applied to the voiced-unvoiced-silence classification in speech processing.

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The article describes the synthesis, structure and magnetic investigations of a series of metal-organic framework compounds formed with Mn+2 and Ni+2 ions. The structures, determined using the single crystal X-ray diffraction, indicated that the structures possess two- and three-dimensional structures with magnetically active dimers, tetramers, chains, two-dimensional layers connected by polycarboxylic acids. These compounds provide good examples for the investigations of magnetic behaviour. Magnetic studies have been carried out using SQUID magnetometer in the range of 2-300 K and the behaviour indicates a predominant anti-ferromagnetic interactions, which appears to differ based on the M-O-C-O-M and/or the M-O-M (M = metal ions) linkages. Thus, compounds with carboxylate (Mn-O-C-O-Mn) connected ones, [C3N2H [Mn(H2O)''C6H3(COO)(3)''], I, [''Mn(H2O (3)''aEuroeC(12)H(8)O(COO)(2)'']center dot H2O, II, [''Mn(H2O)''aEuroeC(12)H(8)O(COO)(2)''], III, show simple anti-ferromagnetic behaviour. The compounds with Mn-O/OH-Mn connected dimer and tetramer units in [NaMn''C6H3(COO)(3)''], IV, [Mn-2(A mu(3)-OH) (H2O)(2)''C6H3(COO)(3)'']center dot 2H(2)O, V, show canted-antiferromagnetic and anti-ferromagnetic behaviour, respectively. The presence of infinite one-dimensional -Ni-OH-Ni- chains in the compound, [Ni-2(H2O)(A mu(3)-OH)(2)(C8H5NO4], VI, gives rise to ferromagnet-like behaviour at low temperatures. The compounds, [Mn-3''C6H3(COO)(3)''(2)], VII and [''Mn(OH)''(2)''C12H8O(COO)(2)''], VIII, have two-dimensional infinite -Mn-O/OH-Mn- layers with triangular magnetic lattices, which resemble the Kagome and brucite-like layer. The magnetic studies indicated canted-antiferromagnetic behaviour in both the cases. Variable temperature EPR and theoretical magnetic modelling studies have been carried out on selected compounds to probe the nature of the magnetic species and their interactions with them.

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In this paper we consider a decentralized supply chain formation problem for linear multi-echelon supply chains when the managers of the individual echelons are autonomous, rational, and intelligent. At each echelon, there is a choice of service providers and the specific problem we solve is that of determining a cost-optimal mix of service providers so as to achieve a desired level of end-to-end delivery performance. The problem can be broken up into two sub-problems following a mechanism design approach: (1) Design of an incentive compatible mechanism to elicit the true cost functions from the echelon managers; (2) Formulation and solution of an appropriate optimization problem using the true cost information. In this paper we propose a novel Bayesian incentive compatible mechanism for eliciting the true cost functions. This improves upon existing solutions in the literature which are all based on the classical Vickrey-Clarke-Groves mechanisms, requiring significant incentives to be paid to the echelon managers for achieving dominant strategy incentive compatibility. The proposed solution, which we call SCF-BIC (Supply Chain Formation with Bayesian Incentive Compatibility), significantly reduces the cost of supply chain formation. We illustrate the efficacy of the proposed methodology using the example of a three echelon manufacturing supply chain.

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We consider the incentive compatible broadcast (ICB) problem in ad hoc wireless networks with selfish nodes. We design a Bayesian incentive compatible Broadcast (BIC-B) protocol to address this problem. VCG mechanism based schemes have been popularly used in the literature to design dominant strategy incentive compatible (DSIC) protocols for ad hoe wireless networks. VCG based mechanisms have two critical limitations: (i) the network is required to he bi-connected, (ii) the resulting protocol is not budget balanced. Our proposed BIC-B protocol overcomes these difficulties. We also prove the optimality of the proposed scheme.

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Considering a general linear model of signal degradation, by modeling the probability density function (PDF) of the clean signal using a Gaussian mixture model (GMM) and additive noise by a Gaussian PDF, we derive the minimum mean square error (MMSE) estimator. The derived MMSE estimator is non-linear and the linear MMSE estimator is shown to be a special case. For speech signal corrupted by independent additive noise, by modeling the joint PDF of time-domain speech samples of a speech frame using a GMM, we propose a speech enhancement method based on the derived MMSE estimator. We also show that the same estimator can be used for transform-domain speech enhancement.

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The metal-organic frameworks, in recent years, show a variety of new developments that includes new methods of preparation, post synthesis modifications and novel class of compounds. Though most of the developments happened in the carboxylate based family of compounds, the other related systems are also equally interesting. In this article,we have highlighted some of the developments that have taken place in the family of non-carboxylate metal-organic frameworks. We have also highlighted some of the recent attempts at modifying the surfaces and pores of the MOFs by careful chemical manipulations. (C) 2009 Elsevier Ltd. All rights reserved.

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The reaction of cadmium sulfate in the presence of polyazaheterocyclic organic molecules gave rise to a variety of new cadmium sulfate phases in water containing solvothermal reaction. The compounds have two- (I) and three-dimensionally (II-VI) extended structures. All the compounds have structures built up by the connectivity involving the cadmium octahedra and the sulfate tetrahedra in which the heterocyclic organic molecules act as the ligand. The linkages between the Cd2+ and (SO4)2- ions form one- (II), two- (I, III, and IV), and three- (V and VI) dimensionally extended cadmium sulfate phases. The connectivity between Cd2+ ion and the heterocyclic ligand also gives rise to one- and two-dimensional structures. The inter-connectivity between the two units gives rise to the observed structures. The presence of Cd-O-Cd chains and Cd-O-Cd layers in some of the structures is noteworthy. The adsorption/desorption studies suggest that the cadmium sulfate phases adsorb/desorb anionic dyes selectively in the presence of water/ethanol, respectively. The photocatalytic degradation studies on cationic dyes under UV-irradiation indicate modest activity. The cyanosilylation of imines using the present compounds as heterogeneous catalyst indicate good catalytic behavior. The various properties exhibited by the cadmium sulfate phases suggest that these compounds are versatile. All the compounds were characterized by powder X-ray diffraction, thermogravimetric analysis, infrared (IR) and UV-visible studies.

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Using first principles calculations, we show the high hydrogen storage capacity of metallacarboranes, where the transition metal (TM) atoms can bind up to 5 H-2-molecules. The average binding energy of similar to 0.3 eV/H favorably lies within the reversible adsorption range. Among the first row TM atoms, Sc and Ti are found to be the optimum in maximizing the H-2 storage (similar to 8 wt %) on the metallacarborane cluster. Being an integral part of the cage, TMs do not suffer from the aggregation problem, which has been the biggest hurdle for the success of TM-decorated graphitic materials for hydrogen storage. Furthermore, the presence of carbon atom in the cages permits linking the metallacarboranes to form metal organic frameworks, which are thus able to adsorb hydrogen via Kubas interaction, in addition to van der Waals physisorption.

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Stochastic behavior of an aero-engine failure/repair process has been analyzed from a Bayesian perspective. Number of failures/repairs in the component-sockets of this multi-component system are assumed to follow independent renewal processes with Weibull inter-arrival times. Based on the field failure/repair data of a large number of such engines and independent Gamma priors on the scale parameters and log-concave priors on the shape parameters, an exact method of sampling from the resulting posterior distributions of the parameters has been proposed. These generated parameter values are next utilised in obtaining the posteriors of the expected number of system repairs, system failure rate, and the conditional intensity function, which are computed using a recursive formula.

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Representation and quantification of uncertainty in climate change impact studies are a difficult task. Several sources of uncertainty arise in studies of hydrologic impacts of climate change, such as those due to choice of general circulation models (GCMs), scenarios and downscaling methods. Recently, much work has focused on uncertainty quantification and modeling in regional climate change impacts. In this paper, an uncertainty modeling framework is evaluated, which uses a generalized uncertainty measure to combine GCM, scenario and downscaling uncertainties. The Dempster-Shafer (D-S) evidence theory is used for representing and combining uncertainty from various sources. A significant advantage of the D-S framework over the traditional probabilistic approach is that it allows for the allocation of a probability mass to sets or intervals, and can hence handle both aleatory or stochastic uncertainty, and epistemic or subjective uncertainty. This paper shows how the D-S theory can be used to represent beliefs in some hypotheses such as hydrologic drought or wet conditions, describe uncertainty and ignorance in the system, and give a quantitative measurement of belief and plausibility in results. The D-S approach has been used in this work for information synthesis using various evidence combination rules having different conflict modeling approaches. A case study is presented for hydrologic drought prediction using downscaled streamflow in the Mahanadi River at Hirakud in Orissa, India. Projections of n most likely monsoon streamflow sequences are obtained from a conditional random field (CRF) downscaling model, using an ensemble of three GCMs for three scenarios, which are converted to monsoon standardized streamflow index (SSFI-4) series. This range is used to specify the basic probability assignment (bpa) for a Dempster-Shafer structure, which represents uncertainty associated with each of the SSFI-4 classifications. These uncertainties are then combined across GCMs and scenarios using various evidence combination rules given by the D-S theory. A Bayesian approach is also presented for this case study, which models the uncertainty in projected frequencies of SSFI-4 classifications by deriving a posterior distribution for the frequency of each classification, using an ensemble of GCMs and scenarios. Results from the D-S and Bayesian approaches are compared, and relative merits of each approach are discussed. Both approaches show an increasing probability of extreme, severe and moderate droughts and decreasing probability of normal and wet conditions in Orissa as a result of climate change. (C) 2010 Elsevier Ltd. All rights reserved.

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This paper considers the problem of spectrum sensing, i.e., the detection of whether or not a primary user is transmitting data by a cognitive radio. The Bayesian framework is adopted, with the performance measure being the probability of detection error. A decentralized setup, where N sensors use M observations each to arrive at individual decisions that are combined at a fusion center to form the overall decision is considered. The unknown fading channel between the primary sensor and the cognitive radios makes the individual decision rule computationally complex, hence, a generalized likelihood ratio test (GLRT)-based approach is adopted. Analysis of the probabilities of false alarm and miss detection of the proposed method reveals that the error exponent with respect to M is zero. Also, the fusion of N individual decisions offers a diversity advantage, similar to diversity reception in communication systems, and a tight bound on the error exponent is presented. Through an analysis in the low power regime, the number of observations needed as a function of received power, to achieve a given probability of error is determined. Monte-Carlo simulations confirm the accuracy of the analysis.

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The impulse response of a typical wireless multipath channel can be modeled as a tapped delay line filter whose non-zero components are sparse relative to the channel delay spread. In this paper, a novel method of estimating such sparse multipath fading channels for OFDM systems is explored. In particular, Sparse Bayesian Learning (SBL) techniques are applied to jointly estimate the sparse channel and its second order statistics, and a new Bayesian Cramer-Rao bound is derived for the SBL algorithm. Further, in the context of OFDM channel estimation, an enhancement to the SBL algorithm is proposed, which uses an Expectation Maximization (EM) framework to jointly estimate the sparse channel, unknown data symbols and the second order statistics of the channel. The EM-SBL algorithm is able to recover the support as well as the channel taps more efficiently, and/or using fewer pilot symbols, than the SBL algorithm. To further improve the performance of the EM-SBL, a threshold-based pruning of the estimated second order statistics that are input to the algorithm is proposed, and its mean square error and symbol error rate performance is illustrated through Monte-Carlo simulations. Thus, the algorithms proposed in this paper are capable of obtaining efficient sparse channel estimates even in the presence of a small number of pilots.

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Layered lanthanide sulfate compounds with three different structures have been prepared and characterized. The compounds C10H10N2] La(SO4)(2)]center dot 2H(2)O (I), C10H10N2] La(SO4)(2)(H2O)(2)](2) (Ha), C10H10N2]Pr(SO4)(2)(H2O)(2)](2) (IIb), C10H10N2]Nd-2(SO4)(4)(H2O)(2)](2) (IIIa), C10H10N2]Sm-2(SO4)(4)(H2O)(2)](2) (IIIb), and C10H10N2]Eu-2(SO4)(4)(H2O)(2)] 2 (IIIC) have anionic lanthanide sulfate layers separated by protonated bipyridine molecules. The layers are formed by the connectivity between the lanthanide polyhedra and sulfate tetrahedra. The formation of a two-dimensional La-O-La layer (la), Pr-O-Pr chains (IIb), and a tetramer cluster (IIIa) is noteworthy. The compounds exhibit honeycomb (I), square (IIa, IIb), and honeycomb (IIIa-IIIc) net arrangements, when the connectivity between the lanthanide ions is considered. Optical studies indicate the observation of characteristic metal-centered emission at room temperature. The Nd compound (IIIa) exhibits a two-photon upconversion behavior.

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Investigations on the reactivity profile of the transient five-membered-ring cyclic carbonyl ylides, generated from alpha-diazo ketones, in the presence of the C=O group of various simple ketones and symrnetrical/unsymmetrical 1,2-diones were carried out. The reaction of alpha-diazo ketones with 1,2-naphthoquinone furnished interesting diastereomeric cycloadducts in which both the C=O groups acted as dipolarophilic sites. The similar reaction in the presence of several isatin derivatives afforded novel spiro dioxa-bridged indole derivatives as a mixture of diastereomers. The single crystal X-ray structure analysis manifestly revealed the mode of cycloaddition and the stereochemistry of two of the diastereomers. A diverse set of novel spiro epoxy-bridged tetrahydropyranone frameworks have been constructed in good yield via the tandem cyclization-cycloaddition of alpha-diazo ketones with the C=O group as heterodipolarophile in a regioselective manner. (C) 2003 Elsevier Ltd. All rights reserved.