954 resultados para Model information


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In this two-part series of papers, a generalized non-orthogonal amplify and forward (GNAF) protocol which generalizes several known cooperative diversity protocols is proposed. Transmission in the GNAF protocol comprises of two phases - the broadcast phase and the cooperation phase. In the broadcast phase, the source broadcasts its information to the relays as well as the destination. In the cooperation phase, the source and the relays together transmit a space-time code in a distributed fashion. The GNAF protocol relaxes the constraints imposed by the protocol of Jing and Hassibi on the code structure. In Part-I of this paper, a code design criteria is obtained and it is shown that the GNAF protocol is delay efficient and coding gain efficient as well. Moreover GNAF protocol enables the use of sphere decoders at the destination with a non-exponential Maximum likelihood (ML) decoding complexity. In Part-II, several low decoding complexity code constructions are studied and a lower bound on the Diversity-Multiplexing Gain tradeoff of the GNAF protocol is obtained.

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In this paper, we introduce the three-user cognitive radio channels with asymmetric transmitter cooperation, and derive achievable rate regions under several scenarios depending on the type of cooperation and decoding capability at the receivers. Two of the most natural cooperation mechanisms for the three-user channel are considered here: cumulative message sharing (CMS) and primary-only message sharing (PMS). In addition to the message sharing mechanism, the achievable rate region is critically dependent on the decoding capability at the receivers. Here, we consider two scenarios for the decoding capability, and derive an achievable rate region for each one of them by employing a combination of superposition and Gel'fand-Pinsker coding techniques. Finally, to provide a numerical example, we consider the Gaussian channel model to plot the rate regions. In terms of achievable rates, CMS turns out to be a better scheme than PMS. However, the practical aspects of implementing such message-sharing schemes remain to be investigated.

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The aim of this study was to evaluate and test methods which could improve local estimates of a general model fitted to a large area. In the first three studies, the intention was to divide the study area into sub-areas that were as homogeneous as possible according to the residuals of the general model, and in the fourth study, the localization was based on the local neighbourhood. According to spatial autocorrelation (SA), points closer together in space are more likely to be similar than those that are farther apart. Local indicators of SA (LISAs) test the similarity of data clusters. A LISA was calculated for every observation in the dataset, and together with the spatial position and residual of the global model, the data were segmented using two different methods: classification and regression trees (CART) and the multiresolution segmentation algorithm (MS) of the eCognition software. The general model was then re-fitted (localized) to the formed sub-areas. In kriging, the SA is modelled with a variogram, and the spatial correlation is a function of the distance (and direction) between the observation and the point of calculation. A general trend is corrected with the residual information of the neighbourhood, whose size is controlled by the number of the nearest neighbours. Nearness is measured as Euclidian distance. With all methods, the root mean square errors (RMSEs) were lower, but with the methods that segmented the study area, the deviance in single localized RMSEs was wide. Therefore, an element capable of controlling the division or localization should be included in the segmentation-localization process. Kriging, on the other hand, provided stable estimates when the number of neighbours was sufficient (over 30), thus offering the best potential for further studies. Even CART could be combined with kriging or non-parametric methods, such as most similar neighbours (MSN).

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Whether proteins denature in all-or-none fashion or in a continuous fashion is as yet an unresolved problem. The all-or-none process implies that while the process of denaturation is going on, only two kinds of protein molecules can exist. One is completely unchanged and the other is altered. The altered protein molecules are indistinguishable. Underlying the 'continuum' models is the assumption that all the chains in a protein globule undergo similar changes so that it is enough to consider a single chain.

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The aim of this dissertation is to model economic variables by a mixture autoregressive (MAR) model. The MAR model is a generalization of linear autoregressive (AR) model. The MAR -model consists of K linear autoregressive components. At any given point of time one of these autoregressive components is randomly selected to generate a new observation for the time series. The mixture probability can be constant over time or a direct function of a some observable variable. Many economic time series contain properties which cannot be described by linear and stationary time series models. A nonlinear autoregressive model such as MAR model can a plausible alternative in the case of these time series. In this dissertation the MAR model is used to model stock market bubbles and a relationship between inflation and the interest rate. In the case of the inflation rate we arrived at the MAR model where inflation process is less mean reverting in the case of high inflation than in the case of normal inflation. The interest rate move one-for-one with expected inflation. We use the data from the Livingston survey as a proxy for inflation expectations. We have found that survey inflation expectations are not perfectly rational. According to our results information stickiness play an important role in the expectation formation. We also found that survey participants have a tendency to underestimate inflation. A MAR model has also used to model stock market bubbles and crashes. This model has two regimes: the bubble regime and the error correction regime. In the error correction regime price depends on a fundamental factor, the price-dividend ratio, and in the bubble regime, price is independent of fundamentals. In this model a stock market crash is usually caused by a regime switch from a bubble regime to an error-correction regime. According to our empirical results bubbles are related to a low inflation. Our model also imply that bubbles have influences investment return distribution in both short and long run.

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We have compared the total as well as fine mode aerosol optical depth (tau and tau(fine)) retrieved by Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua (2001-2005) with the equivalent parameters derived by Aerosol Robotic Network (AERONET) at Kanpur (26.45 degrees N, 80.35 degrees E), northern India. MODIS Collection 005 (C005)-derived tau(0.55) was found to be in good agreement with the AERONET measurements. The tau(fine) and eta (tau(fine)/tau) were, however, biased low significantly in most matched cases. A new set of retrieval with the use of absorbing aerosol model (SSA similar to 0.87) with increased visible surface reflectance provided improved tau and tau(fine) at Kanpur. The new derivation of eta also compares well qualitatively with an independent set of in situ measurements of accumulation mass fraction over much of the southern India. This suggests that though MODIS land algorithm has limited information to derive size properties of aerosols over land, more accurate parameterization of aerosol and surface properties within the existing C005 algorithm may improve the accuracy of size-resolved aerosol optical properties. The results presented in this paper indicate that there is a need to reconsider the surface parameterization and assumed aerosol properties in MODIS C005 algorithm over the Indian region in order to retrieve more accurate aerosol optical and size properties, which are essential to quantify the impact of human-made aerosols on climate.

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Current design models and frameworks describe various overlapping fragments of designing. However, little effort exists in consolidating these fragments into an integrated model. We propose a model of designing that integrates product and process facets of designing by combining activities, outcomes, requirements, and solutions. Validation of the model using video protocols of design sessions demonstrates that all the constructs are used naturally by designers but often not to the expected level, which hinders the variety and resulting novelty of the concepts developed in these sessions. To resolve this, a prescriptive framework for supporting design for variety and novelty is proposed and plans for its implementation are created. DOI: 10.1115/1.3467011]

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A general model of a foam bed reactor has been developed which rigorously accounts for the extent of gas absorption with chemical reaction occurring in both the storage and foam sections. Its applicability extends to a wide spectrum of reaction velocities. The possibilities of the predominance of the bulk-liquid reaction in the storage section or the absorption with reaction in the foam section can be handled as merely special cases of the general analysis. The importance of foam for carrying out a particular gas-liquid reaction is characterised by a criterion in terms of the fractional rate of reaction in the foam section. Trends of variations in the concentrations of dissolved free A, solute B, and gas-phase A with time of operation of the reactor are presented. The nature of the variation in the fractional rate of reaction in the foam section with time, at different reaction velocities, and the effect of the liquid flow rate (across the storage section) on the transience are also illustrated. Finally, the predictions of the general model have been validated using the available experimental data on the oxidation of sodium sulphide in a foam bed reactor. The agreement between the experimental and the present theoretical information is fairly good, apart from being more insightful than all the previous models of this reactor.

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Convolutional network-error correcting codes (CNECCs) are known to provide error correcting capability in acyclic instantaneous networks within the network coding paradigm under small field size conditions. In this work, we investigate the performance of CNECCs under the error model of the network where the edges are assumed to be statistically independent binary symmetric channels, each with the same probability of error pe(0 <= p(e) < 0.5). We obtain bounds on the performance of such CNECCs based on a modified generating function (the transfer function) of the CNECCs. For a given network, we derive a mathematical condition on how small p(e) should be so that only single edge network-errors need to be accounted for, thus reducing the complexity of evaluating the probability of error of any CNECC. Simulations indicate that convolutional codes are required to possess different properties to achieve good performance in low p(e) and high p(e) regimes. For the low p(e) regime, convolutional codes with good distance properties show good performance. For the high p(e) regime, convolutional codes that have a good slope ( the minimum normalized cycle weight) are seen to be good. We derive a lower bound on the slope of any rate b/c convolutional code with a certain degree.

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Scaled Particle Theory (SPT) has been applied to predict the total free energies of micellization of ionic as well as nonionic micellar systems containing an aryl ring. A modification of the previously developed model has been made, proposing a two-zone model of micellar core which corroborates with the structural information available for such systems. The results are in good agreement with experimental data and also confirm the dictating role of cavity forming free energies for such systems

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A number of neural network models, in which fixed-point and limit-cycle attractors of the underlying dynamics are used to store and associatively recall information, are described. In the first class of models, a hierarchical structure is used to store an exponentially large number of strongly correlated memories. The second class of models uses limit cycles to store and retrieve individual memories. A neurobiologically plausible network that generates low-amplitude periodic variations of activity, similar to the oscillations observed in electroencephalographic recordings, is also described. Results obtained from analytic and numerical studies of the properties of these networks are discussed.