Abstract-We present a universal estimator of the divergence ( ) for two arbitrary continuous distributions and satisfying certain regularity conditions. This algorithm, which observes independent and identically distributed (i.i.d.) samples from both and , is based on the estimation of the Radon-Nikodym derivative d d via a data-dependent partition of the observation space. Strong convergence of this estimator is proved with an empirically equivalent segmentation of the space. This basic estimator is further improved by adaptive partitioning schemes and by bias correction. The application of the algorithms to data with memory is also investigated. In the simulations, we compare our estimators with the direct plug-in estimator and estimators based on other partitioning approaches. Experimental results show that our methods achieve the best convergence performance in most of the tested cases.Index Terms-Bias correction, data-dependent partition, divergence, Radon-Nikodym derivative, stationary and ergodic data, universal estimation of information measures.

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This paper presents short-term forecasting model for crude oil prices based on three layer feedforward neural network. Careful attention was paid on finding the optimal network structure. Moreover, a number of features were tested as an inputs such as crude oil futures prices, dollar index, gold spot price, heating oil spot price and S&P 500 index. The results show that with adequate network design and appropriate selection of the training inputs, feedforward networks are capable of forecasting noisy time series with high accuracy.

This paper presents a novel fuzzy logic based approach for the interpretation of texture queries. Tamura feature extraction technique is used to extract each texture feature of an image in the database. A term set on each Tamura feature is generated by a fuzzy clustering algorithm to pose a query in terms of natural language. The query can be expressed as a logic combination of natural language terms and tamura feature values. The performance of the technique was evaluated on Brodatz texture benchmark database. Experimental results show that the proposed technique is effective and the retrieved images indicate that those images are suitable for the specific queries.

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